@conference {cJimenezb, title = {Segmenting Invasive and In Situ Carcinoma in Breast WSIs with a Pretrained Histopathology Transformer}, booktitle = {2nd Deep Breast Workshop on AI and Imaging for Diagnostic and Treatment Challenges in breast care - MICCAI2025}, year = {In Press}, author = {Lauren Jimenez and Felip Vilardel and Ana Petit and Eduard Dorca and Teresa Soler-Mons{\'o} and Irma Ramos-Oliver and Laura Pons and Pedro L. Fern{\'a}ndez and Laia Adalid-Llansa and Daniel Mata and Lourdes Salazar-Huayna and Casas, J. and Ver{\'o}nica Vilaplana} } @article {aSegui, title = {DASPack: Controlled Data Compression for Distributed Acoustic Sensing}, journal = {Geophysical Journal International}, volume = {244}, year = {2026}, month = {01/2026}, abstract = {

We present DASPack, a high-performance, open-source compression tool specifically designed for distributed acoustic sensing (DAS) data. As DAS becomes a key technology for real-time, high-density, and long-range monitoring in fields such as geophysics, infrastructure surveillance, and environmental sensing, the volume of collected data is rapidly increasing. Large-scale DAS deployments already generate hundreds of terabytes and are expected to increase in the coming years, making long-term storage a major challenge. Despite this urgent need, few compression methods have proven to be both practical and scalable in real-world scenarios. DASPack is a fully operational solution that consistently outperforms existing techniques for DAS data. It enables both controlled lossy and lossless compression by allowing users to choose the maximum absolute difference per datum between the original and compressed data. The compression pipeline combines wavelet transforms, linear predictive coding, and entropy coding to optimise efficiency. Our method achieves up to 3X file size reductions for strain and strain rate data in lossless mode across diverse datasets. In lossy mode, compression improves to 6X with near-perfect signal fidelity, and up to 10X is reached with acceptable signal degradation. It delivers fast throughput (100{\textendash}200 MB/s using a single-thread and up to 750 MB/s using 8-threads), enabling real-time deployment even under high data rates. We validated its performance on 15 datasets from a variety of acquisition environments, demonstrating its speed, robustness, and broad applicability. DASPack provides a practical foundation for long-term, sustainable DAS data management in large-scale monitoring networks.

}, keywords = {Distributed Acoustic Sensing, image processing, Probability distributions, Time-series analysis, Wavelet transform}, doi = {https://doi.org/10.1093/gji/ggaf397}, author = {Segu{\'\i}, Aleix and Ugalde, Arantza and Fichtner, Andreas and Ventpsa, Sergi and Morros, J.R.} } @article {aSole25, title = {A Cartesian Encoding Graph Neural Network for Crystal Structures Property Prediction: Application to Thermal Ellipsoid Estimation}, journal = {Digital Discovery}, year = {2025}, month = {01/2025}, doi = {10.1039/D4DD00352G}, author = {Sol{\'e}, A. and Mosella-Montoro, Albert and Cardona, J. and G{\'o}mez-Coca, S. and Aravena, D. and Ruiz, E. and Ruiz-Hidalgo, J.} } @conference {cSaez25, title = {Closing the Loop: Continuous AI Model Improvement Through Pathologist-Guided Feedback}, booktitle = {21st European Congress on Digital Pathology}, year = {2025}, month = {06/2025}, publisher = {The European Society of Digital and Integrative Pathology}, organization = {The European Society of Digital and Integrative Pathology}, address = {Barcelona}, abstract = {

AI integration in digital pathology requires continuous refinement, not just initial deployment. Annotating large datasets is time-consuming, and training an optimal model upfront is impractical. As part of the DigiPatICS project, our approach enables ongoing improvement of deployed algorithms through collaboration between pathologists and data scientists in a structured feedback loop with minimal workflow disruption. This accelerates database growth with task-specific annotations. Moreover, involving different end users reduces bias and enhances diversity and generalizability.

}, url = {https://www.ecdp2025.org/ecdp2025-program.pdf$\#$?page=181}, author = {Laura S{\'a}ez and Sonia Rabanaque and Casas, J. and Marqu{\'e}s, F. and Salembier, P.} } @conference {cMarcello25, title = {Comparative Analysis of Tree Segmentation Techniques on High- and Low-Density LiDAR data}, booktitle = {International Conference on Advanced Remote Sensing (ICARS 2025)}, year = {2025}, month = {03/2025}, publisher = {MDPI}, organization = {MDPI}, address = {Basel, Switzerland}, abstract = {

LiDAR systems are powerful tools for sustainable forest management and ecological research, offering the capability to extract detailed information about canopy structure, tree height, biomass, carbon storage, and biodiversity. Unmanned Aerial Systems (ULSs) mounted on drones provide high spatial resolution, density, and flexibility for capturing detailed forest metrics. Their ability to fly at low altitudes enables the collection of fine-scale details. Conversely, Airborne Laser Scanning (ALS) systems, mounted on aircraft, are ideal for large-scale assessments, despite providing a lower point-cloud density compared to ULSs. This study evaluates individual tree segmentation algorithms in a coniferous forest ecosystem using two data sources: (1) high-density ULS LiDAR data collected with the Zenmuse L1 sensor on a DJI Matrice 300RTK drone, and (2) lower-density ALS LiDAR data from the third coverage of Spain{\textquoteright}s PNOA-LiDAR project (Plan Nacional de Ortofotograf{\'\i}a A{\'e}rea). The general methodology for processing LiDAR data involves preliminary steps to generate Digital Elevation Models (DEMs), Digital Surface Models (DSMs), and Canopy Height Models (CHMs). Subsequently, segmentation techniques are applied to assist tree-level forest analysis. Segmentation is critical for understanding forest structure; however, selecting the most suitable segmentation technique remains an active area of research. To address this issue, a comparative assessment of four commonly used segmentation algorithms (Watershed, Dalponte2016, Silva2016 and Li2012) was conducted using CHMs and normalized 3D point clouds derived from both high- and low-density LiDAR data. Ground-truth reference data were generated by the manual segmentation of individual trees in a representative plot. The results revealed that the Li2012 algorithm demonstrated the best performance in properly segmenting trees in both types of datasets.

}, keywords = {ALS, CHM, forest, LiDAR, tree segmentation, ULS}, url = {https://sciforum.net/paper/view/21619}, author = {Javier Marcello and Mar{\'\i}a Sp{\'\i}nola and Laia Albors and Ferran Marques and Dionisio Rodr{\'\i}guez-Esparrag{\'o}n and Francisco Eugenio} } @article {aCardona25, title = {Exploring Hyperfine Coupling in Molecular Qubits}, journal = {Chemical Science}, year = {2025}, month = {05/2025}, pages = {11291 - 11303}, abstract = {

Molecular qubits represent a promising avenue for advancing quantum sensing and computing technologies, yet significant challenges remain in optimising their performance. Hyperfine coupling has a critical influence on molecular qubit properties. While previous studies have exhaustively investigated this phenomenon, a comprehensive understanding of the underlying mechanisms across different systems remains elusive. A benchmark test was performed using DFT to assess which methodology worked best to accurately predict hyperfine coupling constants in molecular qubits predominantly composed of VIV and CuII. We systematically analysed the decomposition of hyperfine coupling and examined how variations in coordination sphere and molecular geometry impact dipolar, isotropic and spin-orbit contributions. By modelling diverse systems, we demonstrate how molecular design can fine-tune hyperfine coupling contributions, either minimising overall interaction or enhancing coupling along specific axes. This study provides useful insights into the structure-property relationships governing hyperfine coupling mechanisms and assesses the accuracy of different choices of density functional, basis sets and relativistic corrections in the prediction of hyperfine coupling constants.

}, doi = {https://doi.org/10.1039/D5SC02500A}, author = {Cardona, J. and Sol{\'e}, A. and Mella, P. and Aravena, D. and Ruiz-Hidalgo, J. and G{\'o}mez-Coca, S. and Ruiz, E.} } @conference {cLo Anguera25, title = {Leveraging Quantum Machine Learning for Intrusion Detection in Software-Defined Networks}, booktitle = {IEEE International Conference on Machine Learning for Communication and Networking}, year = {2025}, month = {05/2025}, publisher = {IEEE}, organization = {IEEE}, address = {Barcelona}, abstract = {

Quantum machine learning (QML) algorithms\ for intrusion detection systems in software-defined networks are investigated, and their effectiveness is compared with their classical machine learning methods. The University of Nevada - Reno intrusion detection dataset (UNR-IDD) is used to evaluate different QML models, including quantum k-nearest neighbors (QKNNs), quantum support vector machines (QSVMs), quantum neural networks (QNNs), and hybrid quantum neural networks (HQNNs). These models were tested with quantum simulators to evaluate their potential advantages in processing complex datasets. The results show that HQNN and QSVM have higher accuracy than their classical SVM and NN counterparts. This study shows the potential of leveraging QML to enhance precision. References to other works that dive into efficiency and complexity are included.

}, keywords = {Cybersecurity, Intrusion Detection, Quantum machine learning (QML), Software-Defined Networks (SDN)}, doi = {10.5281/zenodo.15784800}, url = {https://icmlcn2025.ieee-icmlcn.org/program/special-sessions}, author = {Joan Lo Anguera and Ruiz-Hidalgo, J. and Sol{\'e}, A. and Casas, J. and Jos{\'e} Antonio L{\'a}zaro and Samuel Sarmiento and Adolfo Ler{\'\i}n} } @conference {cde-Mas-Gimenez25a, title = {Multimodal data acquisition prototype for autonomous driving in adverse weather conditions}, booktitle = {XIV Reuni{\'o}n OptoElectr{\'o}nica (OPTOEL 2025)}, year = {2025}, month = {07/2025}, publisher = {OPTOEL}, organization = {OPTOEL}, address = {Terrassa, Spain}, abstract = {

Autonomous driving has made significant progress in recent years, but adverse weather conditions still remain a major challenge for perception and decision-making algorithms. This work presents a multimodal data acquisition prototype designed to enhance autonomous vehicle perception in challenging environments such as fog, heavy rain, and snow. The system is mounted on a Dacia Duster and features a diverse sensor suite including visible, Short-Wave Infra-Red, thermal, and polarimetric cameras with a solid-state LiDAR and automotive radars. The whole system is calibrated with dedicated calibration boards developed on purpose to enable data fusion across all modalities. Initial results demonstrate the effectiveness of our approach, showing that critical environmental features can be detected reliably across various weather conditions. Future work includes the release of a fully annotated multimodal dataset to support further research in adverse weather perception.

}, isbn = {979-13-87613-54-9}, doi = {10.5821/ebook-9791387613549}, url = {https://optoel.es/2025/wp-content/uploads/2025/07/LIBRO-ACTAS-OPTOEL2025.pdf$\#$?page=403}, author = {Gerard de-Mas-Gim{\'e}nez and Adri{\`a} Subirana and Pablo Garc{\'\i}a-G{\'o}mez and Eduardo Bernal P{\'e}rez and Jordi Riu and Casas, J. and Santiago Royo} } @conference {cde-Mas-Gimenez25, title = {Multimodal sensing prototype for robust autonomous driving under adverse weather conditions}, booktitle = {SPIE Optical Metrology: Optical Measurement Systems for Industrial Inspection XIV}, year = {2025}, month = {06/2025}, publisher = {SPIE}, organization = {SPIE}, address = {Munich, Germany}, abstract = {

Current autonomous driving datasets face significant limitations in adverse weather conditions diversity and sensor generalization. Additionally, commonly used sensors like visible cameras or rotating LiDARs, struggle to perform under harsh weather conditions. To address these challenges, this work introduces a multimodal data acquisition system that integrates high-resolution solid-state LiDAR, automotive RADARs, a combination of visible, thermal, SWIR, and polarimetric cameras, and a GNSS/INS system for odometry and localization. This diverse sensor suite ensures robust performance in low-visibility environments, such as fog or heavy rain, by providing complementary and redundant information. Controlled by an autonomous-safe Nvidia DRIVE AGX with a ROS-based architecture, the system enables precise spatial calibration, temporal synchronization, and realtime data fusion and perception algorithms across an overlapped field of view of 60{\textopenbullet}x 20{\textopenbullet}. With this system, this work aims to publish in the coming months an open-source multimodal labeled dataset for autonomous driving complemented by synthetic data generation through a digital twin in Nvidia{\textquoteright}s Omniverse platform. The data set will have a similar structure as the well-known nuScenes, and will have a similar developer kit to navigate through it with ease. The data set will support a wide range of autonomous driving applications like 3D multimodal object detection and tracking, SLAM, depth completion, and perception enhancement through challenging scenarios.

}, doi = {10.1117/12.3062388}, author = {Gerard de-Mas-Gim{\'e}nez and Adri{\`a} Subirana and Pablo Garc{\'\i}a-G{\'o}mez and Eduardo Bernal P{\'e}rez and Casas, J. and Santiago Royo} } @article {aCumplido-Mayorala, title = {Neuroimaging-derived biological brain age and its associations with glial reactivity and synaptic dysfunction cerebrospinal fluid biomarkers}, journal = {Molecular psychiatry}, year = {2025}, month = {04/2025}, abstract = {

Magnetic resonance Imaging (MRI)-derived brain-age prediction is a promising biomarker of biological brain aging. Accelerated brain aging has been found in Alzheimer{\textquoteright}s disease (AD) and other neurodegenerative diseases. However, no previous studies have investigated the relationship between specific pathophysiological pathways in AD and biological brain aging. Here, we studied whether glial reactivity and synaptic dysfunction are associated with biological brain aging in the earliest stages of the Alzheimer{\textquoteright}s\ continuum, and if these mechanisms are differently associated with AD-related cortical atrophy. We further evaluated their effects on cognitive decline. We included 380 cognitively unimpaired individuals from the ALFA+ study, for which we computed their brain-age deltas by subtracting chronological age from their brain age predicted by machine learning algorithms. We studied the cross-sectional linear associations between brain-age delta and cerebrospinal fluid (CSF) biomarkers of synaptic dysfunction (neurogranin, GAP43, synaptotagmin-1, SNAP25, and α-synuclein), glial reactivity (sTREM2, YKL-40, GFAP, and S100b) and inflammation (interleukin-6). We also studied the cross-sectional linear associations between AD signature and these CSF biomarkers, We further evaluated the mechanisms linking baseline brain-age delta and longitudinal cognitive decline by performing mediation analyses. To reproduce our findings on an independent cohort, we included 152 cognitively unimpaired and 310 mild cognitive impaired (MCI) individuals from the ADNI study. We found that higher CSF sTREM2 was associated with a younger brain-age after adjusting for AD pathology, both in ALFA+ cognitively unimpaired and in ADNI MCI individuals. Furthermore, we found that CSF sTREM2 fully mediated the link between older brain-age and cognitive decline in ALFA+. In summary, we showed that the protective microglial state reflected by higher CSF sTREM2 has a beneficial impact on biological brain aging that may partly explains the variability in cognitive decline in early AD stages, independently of AD pathology.

}, issn = {1359-4184}, doi = {https://doi.org/10.1038/s41380-025-02961-x}, url = {https://www.nature.com/articles/s41380-025-02961-x}, author = {Irene Cumplido-Mayoral and Gonzalo S{\'a}nchez-Benavides and Marta Mil{\`a} Alom{\`a} and Carles Falcon and Raffaele Cacciaglia and Carolina Minguillon and Jose L. Molinuevo and Marc Suarez Calvet and Ver{\'o}nica Vilaplana and Juan D. Gispert} } @conference {cAnguera25, title = {Quantum Machine Learning for Intrusion Detection in Software-Defined Networks}, booktitle = {1st Intl. Workshop on Quantum Computing and Artificial Intelligence (QC+AI 2025) }, year = {2025}, month = {03/2025}, publisher = {Association for the Advancement of Artificial Intelligence (AAAI)}, organization = {Association for the Advancement of Artificial Intelligence (AAAI)}, address = {Philadelphia}, abstract = {

Quantum machine learning (QML) algorithms for intrusion detection systems in software-defined networks are investigated, and their effectiveness is compared with their
classical machine learning methods. The University of Nevada - Reno intrusion detection dataset (UNR-IDD) is used to evaluate different QML models, including quantum k-nearest neighbors (QKNNs), quantum support vector machines (QSVMs), quantum neural networks (QNNs), and hybrid quantum neural networks (HQNNs). These models were tested with quantum simulators to evaluate their potential advantages in processing complex datasets. The results show that HQNN and QSVM have higher accuracy than their classical SVM and NN counterparts.\  This study shows the potential of leveraging QML to enhance precision. References to other works that dive into efficiency and complexity are included.

}, url = {https://sites.google.com/view/qcai2025}, author = {Joan Lo Anguera and Jos{\'e} Antonio L{\'a}zaro and Ruiz-Hidalgo, J. and Sol{\'e}, A. and Casas, J. and Samuel Sarmiento and Adolfo Ler{\'\i}n} } @article {aManjabacas25, title = {Twenty years of AFORO: New developments and connections enhancing otolith research}, journal = {Fisheries Research}, volume = {281}, year = {2025}, month = {01/2025}, abstract = {

Since 2003, with the aim of addressing different issues related to otoliths and the advancement of technologies, AFORO acronym of An{\`a}lisi de FORmes d{\textquoteright}Ot{\`o}lits (otolith shape analysis), a computational environment with a set of tools including a website for this purpose, has gradually expanded its functionality. This implies different ways to measure otoliths in order to obtain different types of information of the same individual. The 2D otoliths shape description using different methods permits the comparison between classical methods and the Wavelet transform, used in the automatic classification system of AFORO. The 3D otoliths description in a few images opens the possibility of classifications using volumetric information, which they have performed well. The data of relationships between otolith and fish length in AFORO is used in predator-prey studies. Our website offers the possibility to display otolith georeferencing information interactively. Furthermore, the automatic classification system has been improved by incorporating geographic filters based on georeferenced data. The diverse information that AFORO offers on the otoliths opens the possibility to approach new studies or to improve the existing ones, combining this information or applying the most appropriate one to the specific problem. Classification cases with Wavelets that have been improved by introducing geographical area information will be presented. In addition, Deep Learning algorithms will be introduced by performing classifications with a small subset of otoliths of species which contain a sufficient number of specimens (\>8).

}, keywords = {artificial intelligence, computer Vision, deep learning, neural networks, Otoliths}, issn = {0165-7836}, doi = {https://doi.org/10.1016/j.fishres.2024.107242}, author = {A. Manjabacas and O. Chic and E. Garc{\'\i}a-Ladona and V.M. Tuset and Morros, J.R. and Elisa Sayrol and P. Mart{\'\i}-Puig and J. Forest and J. Vasconcelos and A. Lombarte} } @conference {cLazaro25, title = {Verifying Key Performance Indicators across Multiple 6G-EWOC Demonstrations}, booktitle = {European Conference on Networks and Communications (EuCNC) }, year = {2025}, month = {06/2025}, publisher = {IEEE}, organization = {IEEE}, address = {Poznan, Poland}, abstract = {

Testing, measuring, and validating Key Performance Indicators (KPIs) are crucial tasks across SNS-JU projects. These activities foster collaboration at the TMV Working Group, enabling the sharing of methods, definitions, target values, and best practices within the 6G vision. Thanks to collaboration of multiple agents, objectives can be different although the main goal of the WG is to develop and mature 6G technology. The 6G-EWOC project aims to describe how KPIs will be verified in different categories through multiple demonstrations. These categories include data rate and capacity in several technologies, sensing, positioning and localization, and energy efficiency. By addressing these different KPIs, the 6G-EWOC project ensures comprehensive evaluation and validation, contributing to the progress of the 6G vision.

}, url = {European\%20Conference\%20on\%20Networks\%20and\%20Communications\%20(EuCNC)}, author = {Jos{\'e} Antonio L{\'a}zaro and Casas, J. and Santiago Royo and Ruiz-Hidalgo, J. and F{\`a}brega, J.M. and Ricardo Mart{\'\i}nez and Renaudier, J. and Mardoyan, H. and Jensen, J.B. and Altab{\'a}s, J.A. and Pablo Garc{\'\i}a-G{\'o}mez and Jordi Riu and Baskopoulos, P. and Kalavrouziotis, D. and Syrivelis, D. and Op de Beeck, C. and Theodoropoulou, E. and Lyberopoulos, G. and Thor, J.} } @conference {cLazaro24, title = {6G-EWOC: Crowdsourced SLAM Data Fusion for Safe and Efficient ADAS Driving}, booktitle = {IEEE Future Networks World Forum: Symposium on Future Networks for Connected and Automated Mobility }, year = {2024}, month = {10/2024}, publisher = {IEEE}, organization = {IEEE}, address = {Dubai}, abstract = {

The development of transport infrastructures for Advanced Driver Assistance Systems (ADAS) and autonomous vehicles operating efficiently and safely in congestion-free traffic flows is a major challenge for telecommunications technologies.\  Simultaneous Localization and Mapping (SLAM) plays a crucial role in ensuring uninterrupted journeys for emergency vehicles and increasing the safety of vulnerable road users in complex traffic scenarios. Accurate SLAM mapping for ADAS systems requires data from different sensor technologies {\textendash}such as high-resolution cameras or Radio/Light Detection and Ranging (RaDAR/LiDAR){\textendash} to be effectively combined or fused. Sensor fusion results in high data throughput and low latency requirements. However, optimal mapping outcomes occur when processing systems fuse data from sensors positioned at different locations within the traffic scene. By crowdsourcing diverse sensors, we can multiply the view angles, mitigate occlusions and improve the overall scene coverage. Yet, this approach introduces additional challenges for communication systems within both the vehicles and the infrastructure. Addressing these challenges is essential for seamless development of safe and efficient ADAS driving techniques.

}, doi = {10.1109/FNWF63303.2024.11028711}, url = {https://ieeexplore.ieee.org/document/11028711}, author = {Jos{\'e} Antonio L{\'a}zaro and Casas, J. and Ruiz-Hidalgo, J. and Cortada-Garcia, M. and Mart{\'\i}n-Pey, G. and Salavedra-Pujol, J. and Wang, M. and Theodoropoulou, E. and Lyberopoulos, G. and Pablo Garc{\'\i}a-G{\'o}mez and S. Royo and Jordi Riu and Marcus, C. and Eriksson, O. and Schrenk, B. and F{\`a}brega, J.M.} } @conference {cSchrenk24, title = {6G-EWOC: Optical Wireless Communication in Support of Autonomous Driving}, booktitle = {IEEE Future Networks World Forum: Symposium on Future Networks for Connected and Automated Mobility }, year = {2024}, month = {10/2024}, publisher = {IEEE}, organization = {IEEE}, address = {Dubai}, abstract = {

The road towards an efficient transport infrastructure, which safely operates fully autonomous vehicles in congestion-free traffic flows, is subject to several technological challenges that reach also into the realm of telecommunications. Future 6G networks are required to handle huge amounts of sensor information, both in terms of low-latency communication and real-time data processing. The 6G-EWOC project contributes to this challenge through a concerted use of optical wireless communication and sensing with radio-frequency based cellular technology. Three optical-wireless scenarios are discussed, including (i) instant data exchange between vehicles leveraging their lighting assets for low-latency communication, (ii) the provision of vehicular data offloading to a fiber-based 6G infrastructure through beamsteering-assisted optical remote radio heads to enable data fusion at the edge cloud, and (iii) the seamless wireless extension of fiber-grade capacity to isolated network segments situated in fiber-scarce brownfields, which is accomplished through transparent optical air interfaces that ensure fiber-grade continuity by preventing a translucent electro-optic termination of the single-mode fiber channel. Another important contribution aims to advance light- and radio-based sensing technologies towards networked versions that offer simultaneous communication and detecting capabilities.

}, doi = {10.1109/FNWF63303.2024.11028710}, url = {https://ieeexplore.ieee.org/document/11028710}, author = {Schrenk, B. and Theodoropoulou, E. and Lyberopoulos, G. and Marcus, C. and Eriksson, O. and Jos{\'e} Antonio L{\'a}zaro and Casas, J. and Federico Dios and Pablo Garc{\'\i}a-G{\'o}mez and S. Royo and Jordi Riu and F{\`a}brega, J.M.} } @article {aGene-Molad, title = {AmodalAppleSize_RGB-D dataset: RGB-D images of apple trees annotated with modal and amodal segmentation masks for fruit detection, visibility and size estimation}, journal = {Data in Brief}, volume = {52}, year = {2024}, month = {02/2024}, abstract = {

The present dataset comprises a collection of RGB-D apple tree images that can be used to train and test computer vision-based fruit detection and sizing methods. This dataset encompasses two distinct sets of data obtained from a Fuji and an Elstar apple orchards. The Fuji apple orchard sub-set consists of 3925 RGB-D images containing a total of 15335 apples annotated with both modal and amodal apple segmentation masks. Modal masks denote the visible portions of the apples, whereas amodal masks encompass both visible and occluded apple regions. Notably, this dataset is the first public resource to incorporate on-tree fruit amodal masks. This pioneering inclusion addresses a critical gap in existing datasets, enabling the development of robust automatic fruit sizing methods and accurate fruit visibility estimation, particularly in the presence of partial occlusions. Besides the fruit segmentation masks, the dataset also includes the fruit size (calliper) ground truth for each annotated apple. The second sub- set comprises 2731 RGB-D images capturing five Elstar apple trees at four distinct growth stages. This sub-set includes mean diameter information for each tree at every growth stage and serves as a valuable resource for evaluating fruit sizing methods trained with the first sub-set. The present data was employed in the research papers titled "Looking behind occlusions: a study on amodal segmentation for robust on-tree apple fruit size estimation" [1] and {\textquotedblleft}Simultaneous fruit detection and size estimation using multitask deep neural networks{\textquotedblright} [2].

}, keywords = {Agricultural robotics, amodal segmentation, depth image, Fruit measurement, Fruit visibility, Instance Segmentation, modal segmentation, Yield prediction}, doi = {https://doi.org/10.1016/j.dib.2023.110000}, author = {Gen{\'e}-Mola, Jordi and Ferrer-Ferrer, M. and Hemming, J. and Dalfsen, P. and Hoog, D. and Sanz-Cortiella, R. and Rosell-Polo, Joan R. and Morros, J.R. and Ver{\'o}nica Vilaplana and Ruiz-Hidalgo, J. and Gregorio, Eduard} } @conference {cAlbors24, title = {An{\'a}lisis multiresoluci{\'o}n espacial del estado de conservaci{\'o}n de un bosque de laurisilvas con sensores pasivos y activos de teledetecci{\'o}n}, booktitle = {XX Congreso de la Asociaci{\'o}n Espa{\~n}ola de Teledetecci{\'o}n}, year = {2024}, month = {06/2024}, publisher = {Universidad de C{\'a}diz}, organization = {Universidad de C{\'a}diz}, address = {C{\'a}diz, Espa{\~n}a}, abstract = {

La conservaci{\'o}n de las zonas naturales es esencial para mantener el equilibrio ecol{\'o}gico de nuestro planeta y preservar la biodiversidad. Estas {\'a}reas desempe{\~n}an un papel fundamental en la regulaci{\'o}n del clima y la provisi{\'o}n de h{\'a}bitats para innumerables especies. En este contexto, la teledetecci{\'o}n se ha convertido en una herramienta valiosa para la gesti{\'o}n sostenible de estos espacios. Espec{\'\i}ficamente, este trabajo aborda la evaluaci{\'o}n del estado de conservaci{\'o}n de un bosque de laurisilvas a partir de datos multiplataforma (sat{\'e}lite, avi{\'o}n y dron) de alta y muy alta resoluci{\'o}n. Se ha realizado un detallado estudio y evaluaci{\'o}n de {\'\i}ndices de vegetaci{\'o}n, se han aplicado los correspondientes procesados, usando modelos avanzados de correcci{\'o}n y clasificaci{\'o}n y se ha generado informaci{\'o}n relativa al estado de salud del ecosistema, a la estructura del dosel arb{\'o}reo y a la distribuci{\'o}n de los sistemas naturales de vegetaci{\'o}n predominantes (bosques de laurisilva y de fayal-brezal). Los resultados de este trabajo est{\'a}n siendo utilizados para el seguimiento ecol{\'o}gico del Parque y para la identificaci{\'o}n de las zonas de desvitalizaci{\'o}n y de p{\'e}rdida de vigor vegetal.

}, keywords = {dron, {\'\i}ndices de vegetaci{\'o}n, laurisilva, LiDAR, salud vegetal, WorldView-2}, url = {http://eo.csic.es/images/yootheme/aet24/Libro\%20ACTAS\%20XX_AET.pdf}, author = {Laia Albors and Mar{\'\i}a Sp{\'\i}nola and Javier Marcello and Ferran Marques and Dionisio Rodr{\'\i}guez-Esparrag{\'o}n and Francisco Eugenio} } @article {aPerez-Cano24, title = {Combining graph neural networks and computer vision methods for cell nuclei classification in lung tissue}, journal = {Heliyon}, volume = {10}, year = {2024}, month = {03/2024}, issn = {2405-8440}, doi = {https://doi.org/10.1016/j.heliyon.2024.e28463}, author = {Jose Perez-Cano and Irene Sansano Valero and D. Anglada and Oscar Pina and Salembier, P. and Marqu{\'e}s, F.} } @conference {cAnglada24, title = {Enhancing Ki-67 Cell Segmentation with Dual U-Net Models: A Step Towards Uncertainty-Informed Active Learning}, booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, year = {2024}, month = {06/2024}, publisher = {IEEE}, organization = {IEEE}, author = {D. Anglada and J. Sala and Marqu{\'e}s, F. and Salembier, P. and M. Pard{\`a}s} } @phdthesis {dSchurholt24, title = {Hyper-Representations: Learning from Populations of Neural Networks}, volume = {PhD}, year = {2024}, month = {05/2024}, abstract = {

Neural Networks (NNs) have undergone a remarkable evolution, transitioning from academic labs to key technologies across various domains. This proliferation underscores their capability and versatility. As these models become integral to critical decision-making processes, the demand for methods to understand their inner workings likewise becomes more pronounced. This thesis addresses the challenge of understanding NNs through the lens of their most fundamental component: the weights, which encapsulate the learned information and determine the model behavior.

The NN weight space contains complex local and global structures which makes it a challenging domain. Addressing these challenges, this thesis develops innovative representation learning methods for the domain of weight spaces. The proposed methods embed and disentangle model weights in a representation space. The representation space allows not only to analyze existing models but also to generate new models with specified characteristics. Such an analysis builds on populations of models, to develop a nuanced understanding of the structure of NN weights.

At the core of this thesis is a fundamental question: Can we learn general, task-agnostic representations from populations of Neural Network models? The key contribution of this thesis to answer that question are hyper-representations, a self-supervised method to learn representations of NN weights. Work in this thesis finds that trained NN models indeed occupy meaningful structures in the weight space, that can be learned and used. Through extensive experiments, this thesis demonstrates that hyper-representations uncover model properties, such as their performance, state of training, or hyperparameters.

Moreover, the identification of regions with specific properties in hyper-representation space allows to sample and generate model weights with targeted properties. This thesis demonstrates applications for fine-tuning, and transfer learning to great success. Lastly, it presents methods that allow hyper-representations to generalize beyond model sizes, architectures, and tasks. The practical implications of that are profound, as it opens the door to foundation models of Neural Networks, which aggregate and instantiate their knowledge across models and architectures.

Ultimately, this thesis contributes to the deeper understanding of Neural Networks by investigating structures in their weights which leads to more interpretable, efficient, and adaptable models. By laying the groundwork for representation learning of NN weights, this research demonstrates the potential to change the way Neural Networks are developed, analyzed, and used.

[My tweet]

Congratulatuon to Dr Konstantin Sch{\

}, author = {Sch{\"u}rholt, Konstantin}, editor = {Mahoney, Michael and Xavier Gir{\'o}-i-Nieto and Borth, Damian} } @conference {ca, title = {Lossless and Lossy Compression for Distributed Acoustic Sensing Using Inter-channel Predictions}, booktitle = {SSA Photonic Seismology 2024}, year = {2024}, month = {10/2024}, address = {Vancouver}, abstract = {

Distributed Acoustic Sensing (DAS) offer unique advantages to extensive monitoring initiatives due to its long-distance, high-density arrays of real-time acoustic sensors. However, high-resolution and long-term applications generate a large amount of data, on the order of hundreds of terabytes per year, presenting challenges for processing and storage. As a result, leveraging innovative data compression techniques is essential for scaling up DAS monitoring. DAS arrays are composed of multiple channels carrying highly correlated and coherent signals. These redundancies allow to exploit inter-channel compression, which use predictions from consecutive channel signals and achieve a higher compression ratio compared to compressing each channel separately.

In this work, we propose a novel coding scheme for DAS data that improves state-of-the-art compression. Encoding follows a pipeline composed of intra-prediction, inter-prediction, transform and entropy coding. For lowly correlated channels, intra-channel prediction is realized by means of Linear Prediction Coding. For inter-channel prediction, we propose three different methods: (1) prediction by warping and scaling the signal from the consecutive channel, (2) a linear predictor is learned over many channels and (3) wavelet transforms are used to disentangle data signals of different frequency, allowing fine-grained prediction. Entropy coding is done by a combination of adaptive arithmetic coding and run-length coding. The implementation is divided into an encoder and a decoder. The encoder uses bitrate optimization for decisions on the prediction methods and parameter values and can be tuned for either speed or high-compression modes. In addition, we explore lossy quantization by adding tunable quantization of the transformed signal, which we observe to achieve significantly higher compression at the expense of quantization noise. The designed algorithms and the provided implementation facilitate the deployment of long-term DAS monitoring.

}, keywords = {Distributed Acoustic Sensing, Signal compression}, url = {https://ssafallmeeting.secure-platform.com/a/gallery/rounds/39/details/12071}, author = {Segu{\'\i}, Aleix and Ugalde, Arantza and Ventosa, Sergi and Morros, J.R.} } @article {aCumplido-Mayoral, title = {The mediating role of neuroimaging-derived biological brain age between risk factors for dementia and cognitive decline in middle/late-aged asymptomatic individuals: a cohort study}, journal = {The Lancet Healthy Longevity}, year = {2024}, month = {04/2024}, abstract = {

Summary Background Neuroimaging-based brain-age delta has been shown to be a mediator linking cardiovascular risk factors to cognitive function. We aimed to assess the mediating role of brain-age delta in the association between modifiable risk factors of dementia and longitudinal cognitive decline in middle-aged and older individuals who are asymptomatic, stratified by Alzheimer{\textquoteright}s disease pathology. We also explored whether the mediation effect is specific to cognitive domain. Methods In this cohort study, we included participants from the ALFA+ cohort aged between 45 years and 65 years who were cognitively unimpaired and who had available structural MRI, cerebrospinal fluid β-amyloid (Aβ)42 and Aβ40 measurements obtained within 1 year of each other, modifiable risk factors assessment, and cognitive evaluation over 3 years. Participants were recruited from the Barcelonaβeta Brain Research Center (Barcelona, Spain). Included individuals underwent a first assessment between Oct 25, 2016, and Jan 28, 2020, and a follow-up cognitive assessment 3{\textperiodcentered}28 (SD 0{\textperiodcentered}27) years later. We computed brain-age delta and composites of different cognitive function domains (preclinical Alzheimer{\textquoteright}s cognitive composite [PACC], attention, executive function, episodic memory, visual processing, and language). We used partial least squares path modelling to explore mediation effects in the associations between modifiable risk factors (including cardiovascular, mental health, mood, metabolic or endocrine history, and alcohol use) and changes in cognitive composites. To assess the role of Alzheimer{\textquoteright}s disease pathology, we computed separate models for Aβ-negative and Aβ-positive individuals. Findings Of the 419 participants enrolled in ALFA+, 302 met our inclusion criteria, of which 108 participants were classified as Aβ-positive and 194 as Aβ-negative. In Aβ-positive individuals, brain-age delta partially mediated (percent mediation proportion 15{\textperiodcentered}73\% [95\% CI 14{\textperiodcentered}22{\textendash}16{\textperiodcentered}66]) the association between modifiable risk factors and decline in overall cognition (across cognitive domains). Brain-age delta fully mediated (mediation proportion 28{\textperiodcentered}03\% [26{\textperiodcentered}25{\textendash}29{\textperiodcentered}21]) the effect of modifiable risk factors on the PACC, wherein increased values for risk factors correlated with an older brain-age delta, and, consequently, an older brain-age delta was linked to greater PACC decline. This effect appears to be primarily driven by memory decline. Mediation was not significant in Aβ-negative individuals (3{\textperiodcentered}52\% [0{\textperiodcentered}072{\textendash}4{\textperiodcentered}17]) on PACC, although path coefficients were not significantly different from those in the Aβ-positive group. Interpretation Our findings suggest that brain-age delta captures the association between modifiable risk factors and longitudinal cognitive decline in middle-aged and older people. In asymptomatic middle-aged and older individuals who are Aβ-positive, the pathology might be the strongest driver of cognitive decline, whereas the effect of risk factors is smaller. Our results highlight the potential of brain-age delta as an objective outcome measure for preventive lifestyle interventions targeting cognitive decline.

}, doi = {10.1016/S2666-7568(24)00025-4}, author = {Irene Cumplido-Mayoral and Anna Brugulat-Serra and Gonzalo S{\'a}nchez-Benavides and Jose Luis Molinuevo and Marc Suarez-Calvet and Ver{\'o}nica Vilaplana and Juan Domingo Gispert} } @article {aMarcello24, title = {Performance of Individual Tree Segmentation Algorithms in Forest Ecosystems Using UAV LiDAR Data}, journal = {Drones}, volume = {8}, year = {2024}, month = {12/2024}, abstract = {

Forests are crucial for biodiversity, climate regulation, and hydrological cycles, requiring sustainable management due to threats like deforestation and climate change. Traditional forest monitoring methods are labor-intensive and limited, whereas UAV LiDAR offers detailed three-dimensional data on forest structure and extensive coverage. This study primarily assesses individual tree segmentation algorithms in two forest ecosystems with different levels of complexity using high-density LiDAR data captured by the Zenmuse L1 sensor on a DJI Matrice 300RTK platform. The processing methodology for LiDAR data includes preliminary preprocessing steps to create Digital Elevation Models, Digital Surface Models, and Canopy Height Models. A comprehensive evaluation of the most effective techniques for classifying ground points in the LiDAR point cloud and deriving accurate models was performed, concluding that the Triangular Irregular Network method is a suitable choice. Subsequently, the segmentation step is applied to enable the analysis of forests at the individual tree level. Segmentation is crucial for monitoring forest health, estimating biomass, and understanding species composition and diversity. However, the selection of the most appropriate segmentation technique remains a hot research topic with a lack of consensus on the optimal approach and metrics to be employed. Therefore, after the review of the state of the art, a comparative assessment of four common segmentation algorithms (Dalponte2016, Silva2016, Watershed, and Li2012) was conducted. Results demonstrated that the Li2012 algorithm, applied to the normalized 3D point cloud, achieved the best performance with an F1-score of 91\% and an IoU of 83\%.

}, keywords = {CHM, Dalponte, DEM, forest, Li, LiDAR, Silva, tree segmentation, ULS, watershed}, issn = {2504-446X}, doi = {10.3390/drones8120772}, url = {https://www.mdpi.com/2504-446X/8/12/772}, author = {Javier Marcello and Mar{\'\i}a Sp{\'\i}nola and Laia Albors and Ferran Marques and Dionisio Rodr{\'\i}guez-Esparrag{\'o}n and Francisco Eugenio} } @conference {cTheodoropoulou24, title = {Towards AI-Enhanced Fibre-Wireless Optical 6G Network in Support of Connected Mobility}, booktitle = {IEEE 29th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)}, year = {2024}, month = {10/2024}, publisher = {IEEE}, organization = {IEEE}, address = {Athens}, abstract = {

The 6G-EWOC project seeks to create an AI-enhanced fiber-wireless optical 6G network to support advanced use cases for Fully Autonomous Vehicles (FAVs) by establishing a new access network incorporating the integration of both fixed/wireless optical and wireless/RF technologies. The access network will be supported by a fast, reconfigurable, highly dynamic and customizable optical fiber-based fronthaul infrastructure which will minimize optoelectronic transitions through tunable and programmable devices, as well as low energy photonic switching of (packet/optical) spectrum and spatial resources, managed by AI-enabled SDN. End-to-end connectivity between AI-based edge computation units will enable advanced Connected and Automated Mobility (CAM) services over a rapid, adaptable network architecture.

}, doi = {10.1109/CAMAD62243.2024.10942755}, url = {https://ieeexplore.ieee.org/document/10942755}, author = {Theodoropoulou, E. and Lyberopoulos, G. and Setaki, Foteini and Pablo Garc{\'\i}a-G{\'o}mez and S. Royo and Marcus, C. and Eriksson, O. and F{\`a}brega, J.M. and Ricardo Mart{\'\i}nez and Ramon Casellas and Schrenk, B. and Casas, J. and Jos{\'e} Antonio L{\'a}zaro} } @article {aCumplido-Mayoral22, title = {Biological Brain Age Prediction Using Machine Learning on Structural Neuroimaging Data: Multi-Cohort Validation Against Biomarkers of Alzheimer{\textquoteright}s Disease and Neurodegeneration stratified by sex}, journal = {eLife}, volume = {12}, year = {2023}, month = {04/2023}, abstract = {

Brain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in neurodegenerative disorders like Alzheimer9s disease (AD), but its validation against markers of neurodegeneration and AD is lacking. Here, imaging-derived measures from the UK Biobank dataset (N=22,661) were used to predict brain-age in 2,314 cognitively unimpaired (CU) individuals at higher risk of AD and mild cognitive impaired (MCI) patients from four independent cohorts with available biomarker data: ALFA+, ADNI, EPAD and OASIS. Brain-age delta was associated with abnormal amyloid-β, more advanced stages (AT) of AD pathology and APOE-ε4 status. Brain-age delta was positively associated with plasma neurofilament light, a marker of neurodegeneration, and sex differences in the brain effects of this marker were found. These results validate brain-age delta as a non-invasive marker of biological brain aging related to markers of AD and neurodegeneration.

}, issn = {2050-084X}, doi = {https://doi.org/10.7554/eLife.81067}, author = {Irene Cumplido-Mayoral and Marina Garc{\'\i}a-Prat and Gregory Operto and Carles Falcon and Mahnaz Shekari and Raffaele Cacciaglia and Marta Mila-Aloma and Luigi Lorenzini and Carolina Minguillon and Jose Luis Molinuevo and Marc Suarez-Calvet and Ver{\'o}nica Vilaplana and Juan Domingo Gispert} } @conference {cCumplido-Mayoral23a, title = {Brain-age mediates the association between modifiable risk factors and cognitive decline early in the AD continuum}, booktitle = {Alzheimer{\textquoteright}s Association International Conference (AAIC)}, year = {2023}, month = {07/2023}, address = {Amsterdam, Netherlands}, author = {Irene Cumplido-Mayoral and Anna Brugulat-Serrat and Gonzalo S{\'a}nchez-Benavides and Armand Gonz{\'a}lez-Escalante and Federica Anastasi and Marta Mila-Aloma and Carles Falcon and Mahnaz Shekari and Raffaele Cacciaglia and Carolina Minguillon and Ver{\'o}nica Vilaplana and Juan D. Gispert} } @conference {cCasamitjana23, title = {Deep Learning CT segmentation for dosimetry in postoperative endometrial carcinoma treatment}, booktitle = {XLI Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, year = {2023}, month = {11/2023}, publisher = {Ediciones UPCT. Universidad Polit{\'e}cnica de Cartagena}, organization = {Ediciones UPCT. Universidad Polit{\'e}cnica de Cartagena}, address = {Cartagena}, abstract = {

Prophylactic vaginal brachytherapy (VBT) is a common treatment after tumor resection in endometrial cancer that requires individual delineation of the Clinical Target Volume (CTV). The main aim of this study was to assess the viability of automatic Deep Learning (DL) algorithms for segmenting the CTV from pelvic Computed Tomography images. We collected a dataset of 220 CT images, labeled manually. We implemented and trained V-Net and UNETR networks and we assessed the performance in a cross-validated setting, by dividing them into training, validation, and test sets. We assessed the quality of the segmentations using the Dice Coefficient (DICE) and the 95\% Hausdorff Distance (HD) and using dose-volume histogram parameters. We also evaluated data augmentation (DA) strategies. Both algorithms gave HD values between 8.2-8.7 and DICE of 0.78-0.79. There were no statistical differences in the volume-dose parameters between automatic and manual labels. DA slightly improved the performance of the algorithms. We proved the
applicability of DL for CTV segmentation in postoperative endometrial carcinoma, using two different model networks, UNETR and V-Net, and with DA.

}, url = {https://caseib.es/2023/wp-content/uploads/2023/11/CASEIB-2023-Programa-Final-Res\%C3\%BAmenes.pdf?$\#$page=39}, author = {Adri{\`a} Casamitjana and Roser Sala-Llonch and Raul Tudela and Arnau Andr{\'e}s and Sara Or{\'\i}o and Casas, J. and Cristian Candela-Juan and Antonio Herreros and Aida Ni{\~n}erola-Baiz{\'a}n} } @article {aPardas23, title = {Stromal tissue segmentation in Ki67 histology images based on cytokeratin-19 stain translation}, journal = {JOURNAL OF MEDICAL IMAGING}, volume = {10}, year = {2023}, month = {06/2023}, abstract = {

Purpose

The diagnosis and prognosis of breast cancer relies on histopathology image analysis. In this context, proliferation markers, especially Ki67, are increasingly important. The diagnosis using these markers is based on the quantification of proliferation, which implies the counting of Ki67 positive and negative tumoral cells in epithelial regions, thus excluding stromal cells. However, stromal cells are often very difficult to distinguish from negative tumoral cells in Ki67 images and often lead to errors when automatic analysis is used.

Approach

We study the use of automatic semantic segmentation based on convolutional neural networks (CNNs) to separate stromal and epithelial areas on Ki67 stained images. CNNs need to be accurately trained with extensive databases with associated ground truth. As such databases are not publicly available, we propose a method to produce them with minimal manual labelling effort. Inspired by the procedure used by pathologists, we have produced the database relying on knowledge transfer from cytokeratin-19 images to Ki67 using an image-to-image (I2I) translation network.

Results

The automatically produced stroma masks are manually corrected and used to train a CNN that predicts very accurate stroma masks for unseen Ki67 images. An F-score value of 0.87 is achieved. Examples of effect on the KI67 score show the importance of the stroma segmentation.

Conclusions

An I2I translation method has proved very useful for building ground-truth labeling in a task where manual labeling is unfeasible. With reduced correction effort, a dataset can be built to train neural networks for the difficult problem of separating epithelial regions from stroma in stained images where separation is very hard without additional information.

}, isbn = {2329-4302}, doi = {https://doi.org/10.1117/1.JMI.10.3.037502}, author = {M. Pard{\`a}s and D. Anglada and M. Espina and F. Marques and Salembier, P.} } @conference {cHurtado23, title = {Study of Manifold Geometry using Multiscale Non-Negative Kernel Graphs}, booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, year = {2023}, month = {06/2023}, address = {Rhodes Island, Greece}, isbn = {978-1-7281-6327-7}, doi = {https://doi.org/10.1109/ICASSP49357.2023.10095956}, author = {Hurtado, C. and Shekkizhar, S. and Ruiz-Hidalgo, J. and Ortega, A.} } @conference {cGene-Mola23, title = {Video-Based Fruit Detection and Tracking for Apple Counting and Mapping}, booktitle = {IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)}, year = {2023}, month = {11/2023}, doi = {10.1109/MetroAgriFor58484.2023.10424135}, author = {Gen{\'e}-Mola, Jordi and Felip-Pom{\'e}s, M. and Net-Barn{\'e}s, F. and Morros, J.R. and Miranda, J. C. and Arn{\'o} Satorra, J. and As{\'\i}n Jones, L. and Lordan Sanahuja, J. and Ruiz-Hidalgo, J. and Gregorio, Eduard} } @conference {cCumplido-Mayoral, title = {Biological Brain Age Prediction Using Machine Learning on Structural Neuroimaging Data: Multi-Cohort Validation Against Biomarkers of Alzheimer{\textquoteright}s Disease and Neurodegeneration}, booktitle = {Alzheimer{\textquoteright}s Association International Conference}, year = {2022}, month = {07/2022}, author = {Irene Cumplido-Mayoral and Marina Garc{\'\i}a-Prat and Greg Operto and Carles Falcon and Mahnaz Shekari and Raffaele Cacciaglia and Marta Mila-Aloma and Marc Suarez Calvet and Ver{\'o}nica Vilaplana and Juan D. Gispert} } @conference {cCumplido-Mayoral22, title = {Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer{\textquoteright}s disease and neurodegeneration stratified by sex}, booktitle = {15th Clinical Trials on Alzheimer{\textquoteright}s Disease Conference (CTAD)}, year = {2022}, month = {11/2022}, address = {San Francisco, USA}, author = {Irene Cumplido-Mayoral and Marta Mila-Aloma and Luigi Lorenzini and Alle Meije Wink and H. Mutsaerts and Sven Haller and Ga{\"e}l Chetelat and Frederik Barkhof and Marc Suarez-Calvet and Ver{\'o}nica Vilaplana and Juan D. Gispert} } @conference {cBonet22, title = {Channel Redundancy and Overlap in Convolutional Neural Networks with Channel-Wise NNK Graphs}, booktitle = {International Conference on Acoustics, Speech and Signal Processing}, year = {2022}, month = {05/2022}, abstract = {

Feature spaces in the deep layers of convolutional neural networks (CNNs) are often very high-dimensional and difficult to interpret. However, convolutional layers consist of multiple channels that are activated by different types of inputs, which suggests that more insights may be gained by studying the channels and how they relate to each other. In this paper, we first analyze theoretically channel-wise non-negative kernel (CW-NNK) regression graphs, which allow us to quantify the overlap between channels and, indirectly, the intrinsic dimension of the data representation manifold. We find that redundancy between channels is significant and varies with the layer depth and the level of regularization during training. Additionally, we observe that there is a correlation between channel overlap in the last convolutional layer and generalization performance. Our experimental results demonstrate that these techniques can lead to a better understanding of deep representations.\ 

}, author = {Bonet, D. and Ortega, A. and Ruiz-Hidalgo, J. and Shekkizhar, S.} } @article {aPedersen22, title = {Experimental confirmation of efficient island divertor operation and successful neoclassical transport optimization in Wendelstein 7-X}, journal = {Nuclear Fusion}, volume = {62}, year = {2022}, month = {04/2022}, issn = {1741-4326}, doi = {10.1088/1741-4326/ac2cf5}, author = {Thomas Sunn Pedersen and al et and Casas, J. and Salembier, P.} } @conference {cSchurholt22, title = {Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights}, booktitle = {NeurIPS 2022 - Neural Information Processing Systems}, year = {2022}, abstract = {

Learning representations of neural network weights given a model zoo is an emerging and challenging area with many potential applications from model inspection, to neural architecture search or knowledge distillation. Recently, an autoencoder trained on a model zoo was able to learn a hyper-representation, which captures intrinsic and extrinsic properties of the models in the zoo. In this work, we extend hyper-representations for generative use to sample new model weights as pre-training. We propose layer-wise loss normalization which we demonstrate is key to generate high-performing models and a sampling method based on the empirical density of hyper-representations. The models generated using our methods are diverse, performant and capable to outperform conventional baselines for transfer learning. Our results indicate the potential of knowledge aggregation from model zoos to new models via hyper-representations thereby paving the avenue for novel research directions.

}, author = {Sch{\"u}rholt, Konstantin and Knyazev, Boris and Xavier Gir{\'o}-i-Nieto and Borth, Damian} } @conference {cSchurholt22a, title = {Model Zoos: A Dataset of Diverse Populations of Neural Network Models}, booktitle = {NeurIPS}, year = {2022}, month = {09/2022}, abstract = {

In the last years, neural networks (NN) have evolved from laboratory environments to the state-of-the-art for many real-world problems. It was shown that NN models (i.e., their weights and biases) evolve on unique trajectories in weight space during training. Following, a population of such neural network models (referred to as model zoo) would form structures in weight space. We think that the geometry, curvature and smoothness of these structures contain information about the state of training and can reveal latent properties of individual models. With such model zoos, one could investigate novel approaches for (i) model analysis, (ii) discover unknown learning dynamics, (iii) learn rich representations of such populations, or (iv) exploit the model zoos for generative modelling of NN weights and biases. Unfortunately, the lack of standardized model zoos and available benchmarks significantly increases the friction for further research about populations of NNs. With this work, we publish a novel dataset of model zoos containing systematically generated and diverse populations of NN models for further research. In total the proposed model zoo dataset is based on eight image datasets, consists of 27 model zoos trained with varying hyperparameter combinations and includes 50{\textquoteright}360 unique NN models as well as their sparsified twins, resulting in over 3,844,360 collected model states. Additionally, to the model zoo data we provide an in-depth analysis of the zoos and provide benchmarks for multiple downstream tasks.

}, author = {Sch{\"u}rholt, Konstantin and Taskiran, Diyar and Knyazev, Boris and Xavier Gir{\'o}-i-Nieto and Borth, Damian} } @conference {cSchurholt22b, title = {Model Zoos: A Dataset of Diverse Populations of Neural Network Models}, booktitle = {NeurIPS 2022 Track Datasets and Benchmarks}, year = {2022}, month = {12/2022}, address = {New Orleans, Louisiana, USA.}, abstract = {

In the last years, neural networks (NN) have evolved from laboratory environments to the state-of-the-art for many real-world problems. It was shown that NN models (i.e., their weights and biases) evolve on unique trajectories in weight space during training. Following, a population of such neural network models (referred to as model zoo) would form structures in weight space. We think that the geometry, curvature and smoothness of these structures contain information about the state of training and can reveal latent properties of individual models. With such model zoos, one could investigate novel approaches for (i) model analysis, (ii) discover unknown learning dynamics, (iii) learn rich representations of such populations, or (iv) exploit the model zoos for generative modelling of NN weights and biases. Unfortunately, the lack of standardized model zoos and available benchmarks significantly increases the friction for further research about populations of NNs. With this work, we publish a novel dataset of model zoos containing systematically generated and diverse populations of NN models for further research. In total the proposed model zoo dataset is based on eight image datasets, consists of 27 model zoos trained with varying hyperparameter combinations and includes 50{\textquoteright}360 unique NN models as well as their sparsified twins, resulting in over 3{\textquoteright}844{\textquoteright}360 collected model states. Additionally, to the model zoo data we provide an in-depth analysis of the zoos and provide benchmarks for multiple downstream tasks.The dataset can be found at www.modelzoos.cc.

}, author = {Sch{\"u}rholt, Konstantin and Taskiran, Diyar and Knyazev, Boris and Xavier Gir{\'o}-i-Nieto and Borth, Damian} } @conference {cPinazo22, title = {Perception in the era of Autonomous Vehicles}, booktitle = {Photonics 4 Smart Cities, SCEWC 2022}, year = {2022}, month = {11/2022}, publisher = {Photonics21}, organization = {Photonics21}, address = {Barcelona}, url = {https://www.fotonica21.org/photonics-4-smart-cities}, author = {Jorge Pinazo and Adolfo Ler{\'\i}n and Francesc Xavier de Gibert and {\'A}lvaro Moliner and Daniel Sevilla and Antonio Jurado and Iv{\'a}n R{\'\i}os and Rodrigo Jerez and Jaime Santiago and {\'A}lvaro Linuesa and Antonio Cano and Federico Dios and Adolfo Comer{\'o}n and Casas, J. and Jos{\'e} Antonio L{\'a}zaro} } @article {cBellver-Bueno20, title = {RefVOS: A Closer Look at Referring Expressions for Video Object Segmentation}, journal = {Multimedia Tools and Applications}, year = {2022}, month = {07/2022}, abstract = {

The task of video object segmentation with referring expressions (language-guided VOS) is to, given a linguistic phrase and a video, generate binary masks for the object to which the phrase refers. Our work argues that existing benchmarks used for this task are mainly composed of trivial cases, in which referents can be identified with simple phrases. Our analysis relies on a new categorization of the phrases in the DAVIS-2017 and Actor-Action datasets into trivial and non-trivial REs, with the non-trivial REs annotated with seven RE semantic categories. We leverage this data to analyze the results of RefVOS, a novel neural network that obtains competitive results for the task of language-guided image segmentation and state of the art results for language-guided VOS. Our study indicates that the major challenges for the task are related to understanding motion and static actions.

}, doi = {https://doi.org/10.1007/s11042-022-13413-x}, author = {Bellver-Bueno, M{\'\i}riam and Ventura, C. and Silberer, Carina and Kazakos, Ioannis and Jordi Torres and Xavier Gir{\'o}-i-Nieto} } @article {aSalgueirob, title = {SEG-ESRGAN: A multi-task network for super-resolution and semantic segmentation of remote sensing images}, journal = {Remote Sensing}, volume = {14}, year = {2022}, month = {2022}, chapter = {5862}, abstract = {

The production of highly accurate land cover maps is one of the primary challenges in remote sensing, which depends on the spatial resolution of the input images. Sometimes, high-resolution imagery is not available or is too expensive to cover large areas or to perform multitemporal analysis. In this context, we propose a multi-task network to take advantage of the freely available Sentinel-2 imagery to produce a super-resolution image, with a scaling factor of 5, and the corresponding high-resolution land cover map. Our proposal, named SEG-ESRGAN, consists of two branches: the super-resolution branch, that produces Sentinel-2 multispectral images at 2 m resolution, and an encoder{\textendash}decoder architecture for the semantic segmentation branch, that generates the enhanced land cover map. From the super-resolution branch, several skip connections are retrieved and concatenated with features from the different stages of the encoder part of the segmentation branch, promoting the flow of meaningful information to boost the accuracy in the segmentation task. Our model is trained with a multi-loss approach using a novel dataset to train and test the super-resolution stage, which is developed from Sentinel-2 and WorldView-2 image pairs. In addition, we generated a dataset with ground-truth labels for the segmentation task. To assess the super-resolution improvement, the PSNR, SSIM, ERGAS, and SAM metrics were considered, while to measure the classification performance, we used the IoU, confusion matrix and the F1-score. Experimental results demonstrate that the SEG-ESRGAN model outperforms different full segmentation and dual network models (U-Net, DeepLabV3+, HRNet and Dual_DeepLab), allowing the generation of high-resolution land cover maps in challenging scenarios using Sentinel-2 10 m bands.

}, issn = {2072-4292 }, doi = {https://doi.org/10.3390/rs142}, url = {https://doi.org/10.3390/rs14225862 }, author = {Luis Salgueiro and Javier Marcello and Ver{\'o}nica Vilaplana} } @phdthesis {dSalgueiro22, title = {Super-resolution and semantic segmentation of remote sensing images using deep learning techniques}, volume = {PhD}, year = {2022}, month = {10/2022}, abstract = {

Remote sensing for Earth observation is a growing scientific field essential for many human activities. Among the different applications in the Remote Sensing domain, the production of thematic maps, such as Land Cover and Land Use, are among the most relevant, as this information plays a critical role in management, planning and monitoring activities at different levels. In this context, the Sentinel-2 satellites are of great importance since they provide open data on land and coastal areas at different spatial resolutions (10, 20, and 60 m), democratizing usability, and creating a high potential for the generation of valuable information, useful in many scenarios, such as agriculture, forestry, land cover and urban planning, among others.

In this thesis, we aim to exploit the usability of Sentinel-2 data by applying deep learning techniques, which are revolutionizing the world of computer vision and, recently, remote sensing. First, we propose super-resolution models to improve the spatial details of the different Sentinel-2 bands, and second, we propose the conjunction of semantic segmentation with super-resolution to generate improved land cover maps that benefit from the enhanced spatial details of the bands.

We first address super-resolution by proposing two different models, one for the 10 m/pixel bands to reach 2 m/pixel and another for the 20 and 60 m/pixel bands to achieve 10 m/pixel. Then, we propose two different multitasking models to derive land cover maps. The first one extending a semantic segmentation model to produce an additional super-resolution image and the second, improving our first super-resolution approach, to provide a semantic segmentation map, as well. We combine features of the different tasks within a single model to improve performance and to generate a high-resolution image with the corresponding highquality land cover map. All models developed were evaluated, quantitatively and qualitatively, using different datasets, showing excellent performance in diverse complex scenarios.

}, author = {Luis Salgueiro}, editor = {Ver{\'o}nica Vilaplana and Javier Marcello} } @conference {cMayoral21a, title = {Brain structural alterations in cognitively unimpaired individuals with discordant amyloid-β PET and CSF Aβ42 status: findings using Machine Learning}, booktitle = {Alzheimer{\textquoteright}s Association International Conference}, year = {2021}, month = {07/2021}, author = {Irene Cumplido-Mayoral and Mahnaz Shekari and Gemma Salvad{\'o} and Greg Operto and Raffaele Cacciaglia and Carles Falcon and Aida Ni{\~n}erola Baiz{\'a}n and Andr{\'e}s Perissinotti and Carolina Minguillon and Karine Fauria and Ivonne Suridjan and Gwendlyn Kollmorgen and Jose Luis Molinuevo and Henrik Zetterberg and Kaj Blennow and Marc Suarez Calvet and Ver{\'o}nica Vilaplana and Juan D. Gispert} } @conference {cBonet21, title = {Channel-Wise Early Stopping without a Validation Set via NNK Polytope Interpolation}, booktitle = {Asia Pacific Signal and Information Processing Association Annual Summit, APSIPA}, year = {2021}, month = {12/2021}, address = {Tokyo, Japan}, abstract = {

State-of-the-art neural network architectures continue to scale in size and deliver impressive generalization results, although this comes at the expense of limited interpretability. In particular, a key challenge is to determine when to stop training the model, as this has a significant impact on generalization. Convolutional neural networks (ConvNets) comprise high-dimensional feature spaces formed by the aggregation of multiple channels, where analyzing intermediate data representations and the model{\textquoteright}s evolution can be challenging owing to the curse of dimensionality. We present channel-wise DeepNNK (CW-DeepNNK), a novel channel-wise generalization estimate based on non-negative kernel regression (NNK) graphs with which we perform local polytope interpolation on low-dimensional channels. This method leads to instance-based interpretability of both the learned data representations and the relationship between channels. Motivated by our observations, we use CW-DeepNNK to propose a novel early stopping criterion that (i) does not require a validation set, (ii) is based on a task performance metric, and (iii) allows stopping to be reached at different points for each channel. Our experiments demonstrate that our proposed method has advantages as compared to the standard criterion based on validation set performance.

}, url = {https://arxiv.org/abs/2107.12972}, author = {Bonet, D. and Ortega, A. and Ruiz-Hidalgo, J. and Shekkizhar, S.} } @mastersthesis {xCaselles21, title = {Disentangling neural network structure from the weights space}, year = {2021}, abstract = {

Deep Neural Networks have been used to tackle a wide variety of tasks achieving great performance. However, there is still a lack of knowledge of how the training of these models converge and how weights relate to their properties. In this thesis we investigate the structure of the weight space and try to disentangle its properties. Attention mechanisms are introduced to capture relations among neurons{\textquoteright} weights that help in weight reconstruction, hyper-parameter classification and accuracy prediction. Our approach further has the potential to work with variable input size allowing different network width, depth or even architecture types.

}, author = {Caselles, Pol}, editor = {Sch{\"u}rholt, Konstantin and Borth, Damian and Xavier Gir{\'o}-i-Nieto} } @article {aAbadal, title = {A Dual Network for Super-Resolution and Semantic Segmentation of Sentinel-2 imagery}, journal = {Remote Sensing}, volume = {13}, year = {2021}, month = {2021}, pages = {4547}, abstract = {

There is a growing interest in the development of automated data processing workflows that provide reliable, high spatial resolution land cover maps. However, high-resolution remote sensing images are not always affordable. Taking into account the free availability of Sentinel-2 satellite data, in this work we propose a deep learning model to generate high-resolution segmentation maps from low-resolution inputs in a multi-task approach. Our proposal is a dual-network model with two branches: the Single Image Super-Resolution branch, that reconstructs a high-resolution version of the input image, and the Semantic Segmentation Super-Resolution branch, that predicts a high-resolution segmentation map with a scaling factor of 2. We performed several experiments to find the best architecture, training and testing on a subset of the S2GLC 2017 dataset. We based our model on the DeepLabV3+ architecture, enhancing the model and achieving an improvement of 5\% on IoU and almost 10\% on the recall score. Furthermore, our qualitative results demonstrate the effectiveness and usefulness of the proposed approach.

}, author = {Sa{\"u}c Abadal and Luis Salgueiro and Javier Marcello and Ver{\'o}nica Vilaplana} } @unpublished {xBonet21, title = {Improved Neural Network Generalization using Channel-Wise NNK Graph Constructions}, year = {2021}, publisher = {Final Year Project, UPC}, abstract = {

State-of-the-art neural network architectures continue to scale in size and deliver impressive results on unseen data points at the expense of poor interpretability. In the deep layers of these models we often encounter very high dimensional feature spaces, where constructing graphs from intermediate data representations can lead to the well-known curse of dimensionality. We propose a channel-wise graph construction method that works on lower dimensional subspaces and provides a new channel-based perspective that leads to better interpretability of the data and relationship between channels. In addition, we introduce a novel generalization estimate based on the proposed graph construction method with which we perform local polytope interpolation. We show its potential to replace the standard generalization estimate based on validation set performance to perform progressive channel-wise early stopping without requiring a validation set.

}, author = {Bonet, David}, editor = {Ortega, Antonio and Ruiz-Hidalgo, J. and Shekkizhar, Sarath} } @conference {cMayoral21, title = {Machine learning on combined neuroimaging and plasma biomarkers for triaging participants of secondary prevention trials in Alzheimer{\textquoteright}s Disease}, booktitle = {Alzheimer{\textquoteright}s Association International Conference}, year = {2021}, month = {07/2021}, author = {Irene Cumplido-Mayoral and Gemma Salvad{\'o} and Mahnaz Shekari and Carles Falcon and Marta Mil{\`a} Alom{\`a} and Aida Ni{\~n}erola Baiz{\'a}n and Jose Luis Molinuevo and Henrik Zetterberg and Kaj Blennow and Marc Suarez Calvet and Ver{\'o}nica Vilaplana and Juan D. Gispert} } @conference {cMayoral21b, title = {Prediction of amyloid pathology in cognitively unimpaired individuals using structural MRI}, booktitle = {Alzheimer{\textquoteright}s Association International Conference}, year = {2021}, month = {07/2021}, author = {Irene Cumplido-Mayoral and Silvia Ingala and Luigi Lorenzini and Alle Meije Wink and Sven Haller and Jose Luis Molinuevo and Robin Wolz and Alessandro Palombit and Adam J Schwarz and Ga{\"e}l Chetelat and Pierre Payoux and Pablo Martinez-Lage and Giovanni Frisoni and Nick C Fox and Craig W Ritchie and Joanna M Wardlaw and Adam Waldman and Frederik Barkhof and Ver{\'o}nica Vilaplana and Juan D. Gispert} } @conference {cPuig-Sitjes21a, title = {Real-time detection of overloads on the PFCs of W7-X}, booktitle = {European Conference on Plasma Diagnostics (ECPD 2021)}, year = {2021}, month = {06/2021}, publisher = {CLPU}, organization = {CLPU}, address = {online}, abstract = {

Wendelstein 7-X (W7-X) is the leading experiment on the path of demonstrating that stellarators are a feasible concept for a future power plant. One of its main goals is to prove quasi-steady-state operation in a reactor-relevant parameter regime. To this end, the surveillance and protection of the water-cooled plasma facing components (PFCs) against overheating is fundamental to guarantee a safe steady-state high-heat-flux operation. The fast reaction times required to prevent damage to the device makes imperative to fully automate the analysis of the thermographic images of the PFCs to detect the thermal events in real-time and timely interrupt operation through the interlock system if a critical event is detected. This imaging system, being the last line of defense, must be based on highly reliable image and risk analysis techniques to guarantee the integrity of the device under all circumstances. During the past operation phases, W7-X was equipped with inertially-cooled test divertor units and although the system still required manual supervision, several concepts to deal with the intrinsic 3D geometry of stellarators were put under test. With the experience gained, a new PFC protection system has been designed based on advanced image segmentation techniques. In order to achieve steady-state operation, however, a feedback control system able to prevent unnecessary interruptions of plasma operation is needed. The feedback control shall be guided by the image analysis, requiring a high-level scene understanding by means of computer vision and machine learning algorithms. Based on this analysis, the feedback control can then take the most effective counter measures to prevent the PFCs overloading by acting on the heating systems, the strike-line shape and positioning or on plasma detachment. In this work, we present the design of the real-time image analysis system for the protection of the PFCs of W7-X through the Interlock, and its validation results based on the analysis of the extensive existing experimental data. Additionally, we present the roadmap towards a feedback control system for the protection of the device in long high-performance plasmas.

}, url = {https://www.clpu.es/en/ECPD2021_Schedule/}, author = {Puig-Sitjes, A. and Jakubowski, M. and Gao, Y. and Drewelow, P. and Niemann, H. and Fellinger, J. and Moncada, V. and Pisano, F. and Belafdil, C. and Mitteau, R. and Aumeunier, M.-H. and Cannas, B. and Casas, J. and Salembier, P. and Clemente, R. and Dumke, S. and Winter, A. and Laqua, H. and Bluhm, T. and Brandt, K.} } @article {aPuig-Sitjes21, title = {Real-time detection of overloads on the plasma-facing components of Wendelstein 7-X}, journal = {Applied sciences (Basel)}, volume = {11}, year = {2021}, month = {12/2021}, chapter = {1}, issn = {2076-3417}, doi = {10.3390/app112411969}, url = {http://hdl.handle.net/2117/361558}, author = {Puig-Sitjes, A. and Jakubowski, M. and Naujoks, D. and Gao, Y. and Drewelow, P. and Niemann, H. and Felinger, J. and Casas, J. and Salembier, P. and Clemente, R.} } @article {aSalgueiroa, title = {Single-image super-resolution of Sentinel-2 low resolution bands with residual dense convolutional neural networks}, journal = {Remote Sensing}, volume = {13}, year = {2021}, month = {2021}, pages = {5007}, abstract = {

Sentinel-2 satellites have become one of the main resources for\  Earth observation images because they are free of charge, have a great spatial coverage and high temporal revisit. Sentinel-2 senses the same location providing different spatial resolutions as well as generating a multi-spectral image with 13 bands of 10, 20, and 60 m/pixel. In this work, we propose a single-image super-resolution model based on convolutional neural networks that enhances the low-resolution bands (20 m and 60 m) to reach the maximal resolution sensed (10 m) at the same time, whereas other approaches provide two independent models for each group of LR bands. Our proposed model, named Sen2-RDSR, is made up of Residual in Residual blocks that produce two final outputs at maximal resolution, one for 20 m/pixel bands and the other for 60 m/pixel bands. The training is done in two stages, first focusing on 20 m bands and then on the 60 m bands. Experimental results using 6 quality metrics (RMSE, SRE, SAM, PSNR, SSIM, ERGAS) show that our model has superior performance compared to other state-of-the-art approaches, and it is very effective and suitable as a preliminary step for land and coastal applications, as studies involving pixel-based classification for Land-Use-Land-Cover or the generation of vegetation indices.

}, author = {Luis Salgueiro and Javier Marcello and Ver{\'o}nica Vilaplana} } @conference {cPuig-Sitjes21, title = {Spatio-temporal Detection and Tracking of Thermal Events on the Plasma Facing Components of Wendelstein 7-X}, booktitle = {4th IAEA Technical Meeting on Fusion Data Processing, Validation and Analysis}, year = {2021}, month = {11/2021}, publisher = {iaea.org}, organization = {iaea.org}, address = {Shanghai (online)}, abstract = {

In steady-state fusion devices like Wendelstein 7-X (W7-X), the active control of heat loads is mandatory to attain long-plasma operation. An intelligent feedback control system that mitigates the risk of overheating is required to avoid a premature plasma termination by the safety system. To keep the plasma within the safe operational limits of the plasma facing components, the feedback control system must be informed of the ongoing thermal events and their evolution in time. Then it can take effectives countermeasures to prevent the thermal events from reaching a critical point. These countermeasures may include reducing the heating power, changing the strike-line position or inducing detachment. With reaction times of the order of a hundred milliseconds, a fully automated real-time image analysis algorithm is required.
In this work, we present a spatio-temporal algorithm to detect, classify and track the thermal events observed by the thermography diagnostic on the plasma facing components of W7-X. The system detects and distinguishes between strike-lines and isolated hot spots as well as leading edges. The segmentation of the strike-line is specially challenging at W7-X. As a 3-dimensional helically-shaped stellarator equipped with 10 island divertors, the strike-lines have a complex heat load distribution with a high-dynamic range. The use of morphological tools and, in particular, the use of the Max-tree transform allow us to segment the thermal events in a hierarchical way preserving the inclusion relationship between different events, like hot spots and leading edges embedded in the strike-line structure. The thermal events are segmented for each frame and tracked over time in order to forecast their temporal evolution and to evaluate their risk. To this end, a spatio-temporal graph is built and spatio-temporal connected components are used to track the thermal events across the sequence frames. The spatio-temporal components in the graph are used to label the events in the sequence preserving temporal coherence and minimizing discontinuities, solving splits and merges. Spatio-temporal descriptors are then generated for each event to assess their risk.
The algorithm was tested offline on the infrared data acquired during the last operation phase OP1.2 and the results are presented here. Further work will follow to accelerate the code with GPUs to reach real-time processing and be ready to protect the water-cooled plasma facing components in the forthcoming operation phase OP2.

}, url = {https://conferences.iaea.org/event/251/contributions/20704/}, author = {Puig-Sitjes, A. and Casas, J. and Salembier, P. and Vizcarro, D. and Clemente, R. and Jakubowski, M. and Gao, Y. and W7-X Team} } @conference {cKazakos, title = {SynthRef: Generation of Synthetic Referring Expressions for Object Segmentation}, booktitle = {NAACL Visually Grounded Interaction and Language (ViGIL) Workshop}, year = {2021}, month = {06/2021}, address = {Virtual}, abstract = {

Recent advances in deep learning have brought significant progress in visual grounding tasks such as language-guided video object segmentation. However, collecting large datasets for these tasks is expensive in terms of annotation time, which represents a bottleneck. To this end, in our work we propose a novel method, namely SynthRef, for generating synthetic referring expressions for an image (or video frame), and we also present and disseminate the first large-scale dataset with synthetic referring expressions for video object segmentation. Our experiments demonstrate that by training with our synthetic dataset one can improve the ability of a model to generalize across different datasets, without any additional annotation cost. Moreover, our formulation allows its application to any object detection or segmentation dataset.

}, author = {Kazakos, Ioannis and Bellver-Bueno, M{\'\i}riam and Ventura, C. and Silberer, Carina and Xavier Gir{\'o}-i-Nieto} } @conference {cFernandezf, title = {Enhancing Online Knowledge Graph Population with Semantic Knowledge}, booktitle = {19th International Semantic Web Conference (ISWC)}, year = {2020}, month = {11/2020}, address = {Virtual}, abstract = {

Knowledge Graphs (KG) are becoming essential to organize, represent and store the world{\textquoteright}s knowledge, but they still rely heavily on humanly-curated structured data. Information Extraction (IE) tasks, like disambiguating entities and relations from unstructured text, are key to automate KG population. However, Natural Language Processing (NLP) methods alone can not guarantee the validity of the facts extracted and may introduce erroneous information into the KG.\ This work presents an end-to-end system that combines Semantic Knowledge and Validation techniques with NLP methods, to provide KG population of novel facts from clustered news events.\ The contributions of this paper are two-fold: First, we present a novel method for including entity-type knowledge into a Relation Extraction model, improving F1-Score over the baseline with TACRED and TypeRE datasets. Second, we increase the precision by adding data validation on top of the Relation Extraction method. These two contributions are combined in an industrial pipeline for automatic KG population over aggregated news, demonstrating increased data validity when performing online learning from unstructured web data. Finally, the TypeRE and AggregatedNewsRE datasets build to benchmark these results are also published to foster future research in this field.

}, keywords = {Data Validation, Knowledge Graph, Relation Extraction}, author = {Fern{\`a}ndez, D{\`e}lia and Rimmek, Joan Marco and Espadaler, Joan and Garolera, Blai and Barja, Adri{\`a} and Codina, Marc and Sastre, Marc and Xavier Gir{\'o}-i-Nieto and Riveiro, Juan Carlos and Bou-Balust, Elisenda} } @conference {cCamposb, title = {Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills}, booktitle = {International Conference on Machine Learning (ICML) 2020}, year = {2020}, month = {07/2020}, abstract = {

Acquiring abilities in the absence of a task-oriented reward function is at the frontier of reinforcement learning research. This problem has been studied through the lens of empowerment, which draws a connection between option discovery and information theory. Information-theoretic skill discovery methods have garnered much interest from the community, but little research has been conducted in understanding their limitations. Through theoretical analysis and empirical evidence, we show that existing algorithms suffer from a common limitation -- they discover options that provide a poor coverage of the state space. In light of this, we propose {\textquoteright}Explore, Discover and Learn{\textquoteright} (EDL), an alternative approach to information-theoretic skill discovery. Crucially, EDL optimizes the same information-theoretic objective derived from the empowerment literature, but addresses the optimization problem using different machinery. We perform an extensive evaluation of skill discovery methods on controlled environments and show that EDL offers significant advantages, such as overcoming the coverage problem, reducing the dependence of learned skills on the initial state, and allowing the user to define a prior over which behaviors should be learned.




}, author = {V{\'\i}ctor Campos and Trott, Alexander and Xiong, Caiming and Socher, Richard and Xavier Gir{\'o}-i-Nieto and Jordi Torres} } @article {aGene-Molac, title = {Fruit detection and 3D location using instance segmentation neural networks and structure-from-motion photogrammetry}, journal = {Computers and Electronics in Agriculture}, volume = {169}, year = {2020}, month = {02/2020}, abstract = {

The development of remote fruit detection systems able to identify and 3D locate fruits provides opportunities to improve the efficiency of agriculture management. Most of the current fruit detection systems are based on 2D image analysis. Although the use of 3D sensors is emerging, precise 3D fruit location is still a pending issue. This work presents a new methodology for fruit detection and 3D location consisting of: (1) 2D fruit detection and segmentation using Mask R-CNN instance segmentation neural network; (2) 3D point cloud generation of detected apples using structure-from-motion (SfM) photogrammetry; (3) projection of 2D image detections onto 3D space; (4) false positives removal using a trained support vector machine. This methodology was tested on 11 Fuji apple trees containing a total of 1455 apples. Results showed that, by combining instance segmentation with SfM the system performance increased from an F1-score of 0.816 (2D fruit detection) to 0.881 (3D fruit detection and location) with respect to the total amount of fruits. The main advantages of this methodology are the reduced number of false positives and the higher detection rate, while the main disadvantage is the high processing time required for SfM, which makes it presently unsuitable for real-time work. From these results, it can be concluded that the combination of instance segmentation and SfM provides high performance fruit detection with high 3D data precision. The dataset has been made publicly available and an interactive visualization of fruit detection results is accessible at http://www.grap.udl.cat/documents/photogrammetry_fruit_detection.html

}, keywords = {Fruit detection, Fruit location, Mask R-CNN, Structure-from-motion, Terrestrial remote sensing}, issn = {ISSN: 0168-1699}, doi = {https://doi.org/10.1016/j.compag.2019.105165}, url = {https://doi.org/10.1016/j.compag.2019.105165}, author = {Gen{\'e}-Mola, Jordi and Sanz, Ricardo and Rosell-Polo, Joan R. and Morros, J.R. and Ruiz-Hidalgo, J. and Ver{\'o}nica Vilaplana and Gregorio, Eduard} } @article {aGene-Mola20, title = {Fuji-SfM dataset: A collection of annotated images and point clouds for Fuji apple detection and location using structure-from-motion photogrammetry}, volume = {Data in Brief}, year = {2020}, month = {06/2020}, keywords = {Fruit detection, Mask R-CNN, Photogrammetry, Structure-from-motion, Terrestrial remote sensing, Yield mapping, Yield prediction}, doi = {https://doi.org/10.1016/j.dib.2020.105591}, author = {Gen{\'e}-Mola, Jordi and Sanz, Ricardo and Rosell-Polo, Joan R. and Morros, J.R. and Ruiz-Hidalgo, J. and Ver{\'o}nica Vilaplana and Gregorio, Eduard} } @article {9103248, title = {Grounded Sequence to Sequence Transduction}, journal = {IEEE Journal of Selected Topics in Signal Processing}, volume = {14}, year = {2020}, month = {05/2020}, pages = {577-591}, abstract = {

Speech recognition and machine translation have made major progress over the past decades, providing practical systems to map one language sequence to another. Although multiple modalities such as sound and video are becoming increasingly available, the state-of-the-art systems are inherently unimodal, in the sense that they take a single modality {\textemdash} either speech or text {\textemdash} as input. Evidence from human learning suggests that additional modalities can provide disambiguating signals crucial for many language tasks. In this article, we describe the How2 dataset\ , a large, open-domain collection of videos with transcriptions and their translations. We then show how this single dataset can be used to develop systems for a variety of language tasks and present a number of models meant as starting points. Across tasks, we find that building multimodal architectures that perform better than their unimodal counterpart remains a challenge. This leaves plenty of room for the exploration of more advanced solutions that fully exploit the multimodal nature of the How2 dataset\ , and the general direction of multimodal learning with other datasets as well.

}, author = {L. Specia and L. Barrault and O. Caglayan and Amanda Duarte and D. Elliott and S. Gella and N. Holzenberger and C. Lala and S. J. Lee and J. Libovicky and P. Madhyastha and F. Metze and K. Mulligan and A. Ostapenko and S. Palaskar and R. Sanabria and J. Wang and R. Arora} } @article {aBellver, title = {Mask-guided sample selection for Semi-Supervised Instance Segmentation}, journal = {Multimedia Tools and Applications}, year = {2020}, month = {07/2020}, abstract = {

Image segmentation methods are usually trained with pixel-level annotations, which require significant human effort to collect. The most common solution to address this constraint is to implement weakly-supervised pipelines trained with lower forms of supervision, such as bounding boxes or scribbles. Another option are semi-supervised methods, which leverage a large amount of unlabeled data and a limited number of strongly-labeled samples. In this second setup, samples to be strongly-annotated can be selected randomly or with an active learning mechanism that chooses the ones that will maximize the model performance.\ In this work, we propose a sample selection approach to decide which samples to annotate for semi-supervised instance segmentation. Our method consists in first predicting pseudo-masks for the unlabeled pool of samples, together with a score predicting the quality of the mask. This score is an estimate of the Intersection Over Union (IoU) of the segment with the ground truth mask. We study which samples are better to annotate given the quality score, and show how our approach outperforms a random selection, leading to improved performance for semi-supervised instance segmentation with low annotation budgets.

}, doi = {10.1007/s11042-020-09235-4}, url = {http://link.springer.com/article/10.1007/s11042-020-09235-4}, author = {M{\'\i}riam Bellver and Amaia Salvador and Jordi Torres and Xavier Gir{\'o}-i-Nieto} } @conference {cPuig-Sitjes20, title = {Strategy for the real-time detection of thermal events on the plasma facing components of Wendelstein 7-X}, booktitle = {31st Symposium on Fusion Technology (SOFT2020)}, year = {2020}, month = {09/2020}, address = {Dubrovnik, Croatia}, abstract = {

Wendelstein 7-X (W7-X), the most advanced fusion experiment in the stellarator line, aims at demonstrating the feasibility of the stellarator concept as a future fusion power plant. It is planned to restart operation by the end of 2021 with a high heat flux divertor and water-cooled plasma facing components (PFCs) to demonstrate steady-state operation. With plasma energy limits starting at 1 GJ and gradually increasing to 18 GJ over several experimental campaigns, the PFCs have to be protected from overheating. For that, a fully autonomous system is required in order to prevent damage to the plasma facing components due to thermal events.
During the last experimental campaign, when W7-X was equipped with inertially cooled test divertor units, extensive experience was gained with the preliminary design of the thermal event detection system. By then, the system was not yet real-time capable and it was not fully automated, requiring manual supervision between discharges. This experience, however, allowed to prove the validity of some design concepts and to define the new strategy towards the protection of the machine in steady-state operation, when the system will be connected to the Interlock System and the feedback control.
In this work, the design of the real-time thermal event detection system for W7-X for steady-state operation is presented. The system is based on the thermography and video diagnostics to monitor the divertor units, the baffles, and the wall heat-shields and panels. It will be implemented on a real-time system and integrated in CoDaC{\textquoteright}s safety infrastructure. The system relies on computer vision and machine learning techniques to perform a spatio-temporal analysis to detect and classify the thermal events and to perform a risk evaluation. The results and the main conclusions drawn from the analysis of the data from the past campaign are reported.

}, url = {http://hdl.handle.net/21.11116/0000-0007-7FF5-7}, author = {Puig-Sitjes, A. and Jakubowski, M. and Fellinger, J. and Drewelow, P. and Gao, Y. and Niemann, H. and Sunn-Pedersen, T. and K{\"o}nig, R. and Naujoks, D. and Winter, A. and Laqua, H. and Dumke, S. and Moncada, V. and Belafdil, C. and Mitteau, R. and Aumeunier, M.-H. and Pisano, F. and Aymerich, E. and Cannas, B. and Kocsis, G. and Szepesi, T. and Cseh, G. and Szabolics, T. and Casas, J. and Morros, J.R. and Salembier, P. and Clemente, R. and Cobos, M. and I. Caminal and Palacios Corral, A. and Moreno Punzano, A. and Quiceno Lopera, S.} } @article {aSalgueiro, title = {Super-Resolution of Sentinel-2 Imagery Using Generative Adversarial Networks}, journal = {Remote Sensing}, volume = {12}, year = {2020}, month = {01/2020}, abstract = {

Sentinel-2 satellites provide multi-spectral optical remote sensing images with four bands at 10 m of spatial resolution. These images, due to the open data distribution policy, are becoming an important resource for several applications. However, for small scale studies, the spatial detail of these images might not be sufficient. On the other hand, WorldView commercial satellites offer multi-spectral images with a very high spatial resolution, typically less than 2 m, but their use can be impractical for large areas or multi-temporal analysis due to their high cost. To exploit the free availability of Sentinel imagery, it is worth considering deep learning techniques for single-image super-resolution tasks, allowing the spatial enhancement of low-resolution (LR) images by recovering high-frequency details to produce high-resolution (HR) super-resolved images. In this work, we implement and train a model based on the Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) with pairs of WorldView-Sentinel images to generate a super-resolved multispectral Sentinel-2 output with a scaling factor of 5. Our model, named RS-ESRGAN, removes the upsampling layers of the network to make it feasible to train with co-registered remote sensing images. Results obtained outperform state-of-the-art models using standard metrics like PSNR, SSIM, ERGAS, SAM and CC. Moreover, qualitative visual analysis shows spatial improvements as well as the preservation of the spectral information, allowing the super-resolved Sentinel-2 imagery to be used in studies requiring very high spatial resolution.

}, author = {Luis Salgueiro and Javier Marcello and Ver{\'o}nica Vilaplana} } @conference {cMoliner, title = {Weakly Supervised Semantic Segmentation for Remote Sensing Hyperspectral Imaging}, booktitle = {International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020)}, year = {2020}, month = {05/2020}, abstract = {

This paper studies the problem of training a semantic segmentation neural network with weak annotations, in order to be applied in aerial vegetation images from Teide National Park. It proposes a Deep Seeded Region Growing system which consists on training a semantic segmentation network from a set of seeds generated by a Support Vector Machine. A region growing algorithm module is applied to the seeds to progressively increase the pixel-level supervision. The proposed method performs better than an SVM, which is one of the most popular segmentation tools in remote sensing image applications.

}, author = {Eloi Moliner and Luis Salgueiro and Ver{\'o}nica Vilaplana} } @article {aWang19, title = {Benchmark on Automatic 6-month-old Infant Brain Segmentation Algorithms: The iSeg-2017 Challenge}, journal = {IEEE Transactions on Medical Imaging}, year = {2019}, month = {2019/2/27}, abstract = {

Accurate segmentation of infant brain magnetic resonance (MR) images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) is an indispensable foundation for early studying of brain growth patterns and morphological changes in neurodevelopmental disorders. Nevertheless, in the isointense phase (approximately 6-9 months of age), due to inherent myelination and maturation process, WM and GM exhibit similar levels of intensity in both T1-weighted (T1w) and T2-weighted (T2w) MR images, making tissue segmentation very challenging. Despite many efforts were devoted to brain segmentation, only few studies have focused on the segmentation of 6-month infant brain images. With the idea of boosting methodological development in the community, iSeg-2017 challenge (http://iseg2017.web.unc.edu) provides a set of 6-month infant subjects with manual labels for training and testing the participating methods. Among the 21 automatic segmentation methods participating in iSeg-2017, we review the 8 top-ranked teams, in terms of Dice ratio, modified Hausdorff distance and average surface distance, and introduce their pipelines, implementations, as well as source codes. We further discuss limitations and possible future directions. We hope the dataset in iSeg-2017 and this review article could provide insights into methodological development for the community.

}, doi = {10.1109/TMI.2019.2901712}, author = {Li Wang and Dong Nie and Guannan Li and Elodie Puybareau and Jose Dolz and Qian Zhang and Fan Wang and Jing Xia and Zhengwang Wu and Jiawei Chen and Kim-HanThung and Toan Duc Bui and Jitae Shin and Guodong Zeng and Guoyan Zheng and Vladimir S. Fonov and Andrew Doyle and Yongchao Xu and Pim Moeskops and Josien Pluim and Christian Desrosiers and Ismail Ben Ayed and Gerard Sanroma and Oualid Benkarim and Adri{\`a} Casamitjana and Ver{\'o}nica Vilaplana and Weili Lin and Gang Li and Dinggang Shen} } @conference {cBellverb, title = {Budget-aware Semi-Supervised Semantic and Instance Segmentation}, booktitle = {CVPR 2019 DeepVision Workshop}, year = {2019}, month = {05/2019}, publisher = {OpenCVF}, organization = {OpenCVF}, address = {Long Beach, CA, USA}, abstract = {

Methods that move towards less supervised scenarios are key for image segmentation, as dense labels demand significant human intervention. Generally, the annotation burden is mitigated by labeling datasets with weaker forms of supervision, e.g. image-level labels or bounding boxes. Another option are semi-supervised settings, that commonly leverage a few strong annotations and a huge number of unlabeled/weakly-labeled data. In this paper, we revisit semi-supervised segmentation schemes and narrow down significantly the annotation budget (in terms of total labeling time of the training set) compared to previous approaches. With a very simple pipeline, we demonstrate that at low annotation budgets, semi-supervised methods outperform by a wide margin weakly-supervised ones for both semantic and instance segmentation. Our approach also outperforms previous semi-supervised works at a much reduced labeling cost. We present results for the Pascal VOC benchmark and unify weakly and semi-supervised approaches by considering the total annotation budget, thus allowing a fairer comparison between methods.

Winners of the best paper award at the $\#$CVPR2019 DeepVision workshop

Budget-aware Semi-Supervised Semantic and Instance Segmentation from Universitat Polit{\`e}cnica de Catalunya
}, url = {https://arxiv.org/abs/1905.05880}, author = {M{\'\i}riam Bellver and Amaia Salvador and Jordi Torres and Xavier Gir{\'o}-i-Nieto} } @conference {cIsart, title = {CNN-based bacilli detection in sputum samples for tuberculosis diagnosis}, booktitle = {International Symposium on Biomedical Imaging (ISBI 2019)}, year = {2019}, month = {04/2019}, abstract = {

Tuberculosis (TB) is one of the infectious diseases that causes more deaths in low and middle-income countries. A low-cost method to diagnose TB consists in analyzing sputum smear samples through microscope observation. Manual identification and counting of bacilli is a very time consuming task and the sensitivity of the diagnosis depends on the availability of skilled technicians. We propose a computer vision technique based on a convolutional neural network (CNN) to automatically segment and count bacilli in sputum samples and predict the infection level.

}, author = {Antoni Isart and Mateu Espasa and Ver{\'o}nica Vilaplana and Elisa Sayrol} } @conference {cSalgueiro, title = {Comparative study of upsampling methods for super-resolution in remote sensing}, booktitle = {International Conference on Machine Vision}, year = {2019}, month = {11/2019}, abstract = {

Many remote sensing applications require high spatial resolution images, but the elevated cost of these images makes some studies unfeasible. Single-image super-resolution algorithms can improve the spatial resolution of a low-resolution image by recovering feature details learned from pairs of low-high resolution images. In this work, several configurations of ESRGAN, a state-of-the-art algorithm for image super-resolution are tested. We make a comparison between several scenarios, with different modes of upsampling and channels involved.\  The best results are obtained training a model with RGB-IR channels and using progressive upsampling.\ 

}, keywords = {deep learning, Remote sensing, Super-resolution, WorldView-2}, author = {Luis Salgueiro and Javier Marcello and Ver{\'o}nica Vilaplana} } @phdthesis {dSalvador, title = {Computer Vision beyond the visible: Image understanding through language}, volume = {Phd}, year = {2019}, school = {Universitat Politecnica de Catalunya}, address = {Barcelona}, abstract = {

In the past decade, deep neural networks have revolutionized computer vision. High performing deep neural architectures trained for visual recognition tasks have pushed the field towards methods relying on learned image representations instead of hand-crafted ones, in the seek of designing end-to-end learning methods to solve challenging tasks, ranging from long-lasting ones such as image classification to newly emerging tasks like image captioning.\ 

As this thesis is framed in the context of the rapid evolution of computer vision, we present contributions that are aligned with three major changes in paradigm that the field has recently experienced, namely 1) the power of re-utilizing deep features from pre-trained neural networks for different tasks, 2) the advantage of formulating problems with end-to-end solutions given enough training data, and 3) the growing interest of describing visual data with natural language rather than pre-defined categorical label spaces, which can in turn enable visual understanding beyond scene recognition.

The first part of the thesis is dedicated to the problem of visual instance search, where we particularly focus on obtaining meaningful and discriminative image representations which allow efficient and effective retrieval of similar images given a visual query. Contributions in this part of the thesis involve the construction of sparse Bag-of-Words image representations from convolutional features from a pre-trained image classification neural network, and an analysis of the advantages of fine-tuning a pre-trained object detection network using query images as training data.

The second part of the thesis presents contributions to the problem of image-to-set prediction, understood as the task of predicting a variable-sized collection of unordered elements for an input image. We conduct a thorough analysis of current methods for multi-label image classification, which are able to solve the task in an end-to-end manner by simultaneously estimating both the label distribution and the set cardinality. Further, we extend the analysis of set prediction methods to semantic instance segmentation, and present an end-to-end recurrent model that is able to predict sets of objects (binary masks and categorical labels) in a sequential manner.

Finally, the third part of the dissertation takes insights learned in the previous two parts in order to present deep learning solutions to connect images with natural language in the context of cooking recipes and food images. First, we propose a retrieval-based solution in which the written recipe and the image are encoded into compact representations that allow the retrieval of one given the other. Second, as an alternative to the retrieval approach, we propose a generative model to predict recipes directly from food images, which first predicts ingredients as sets and subsequently generates the rest of the recipe one word at a time by conditioning both on the image and the predicted ingredients.

}, url = {https://www.tdx.cat/handle/10803/667162}, author = {Amaia Salvador}, editor = {Xavier Gir{\'o}-i-Nieto and Marqu{\'e}s, F.} } @mastersthesis {xBalibrea19, title = {Deep learning for semantic segmentation of airplane hyperspectral imaging}, year = {2019}, abstract = {

Given their success, both qualitative and quantitative, Deep Neural Networks have been used to approach classification and segmentation problems for images, especially during these last few years where it has been possible to design computers with sufficient capacity to make quick and efficient experiments.

In this work, we will study the use of two Convolutional Neural Networks (CNNs) to segment the ground of a land section of Maspalomas{\textquoteright} Park using an image taken by the flight of an airplane.

The comparison will be made in terms of computational cost, complexity and results that will be obtained while testing different algorithms, loss functions or optimizers and also while tuning some other parameters. The results will also be compared with a past work done with the same dataset but another methodology (SVM).

}, author = {Mar Balibrea}, editor = {Luis Salgueiro and Ver{\'o}nica Vilaplana} } @article {aLin19, title = {Depth Estimation and Semantic Segmentation from a Single RGB Image Using a Hybrid Convolutional Neural Network}, journal = {Sensors}, volume = {19}, year = {2019}, month = {04/2019}, chapter = {1795}, abstract = {

Semantic segmentation and depth estimation are two important tasks in computer vision, and many methods have been developed to tackle them. Commonly these two tasks are addressed independently, but recently the idea of merging these two problems into a sole framework has been studied under the assumption that integrating two highly correlated tasks may benefit each other to improve the estimation accuracy. In this paper, depth estimation and semantic segmentation are jointly addressed using a single RGB input image under a unified convolutional neural network. We analyze two different architectures to evaluate which features are more relevant when shared by the two tasks and which features should be kept separated to achieve a mutual improvement. Likewise, our approaches are evaluated under two different scenarios designed to review our results versus single-task and multi-task methods. Qualitative and quantitative experiments demonstrate that the performance of our methodology outperforms the state of the art on single-task approaches, while obtaining competitive results compared with other multi-task methods.

}, keywords = {depth estimation; semantic segmentation; convolutional neural networks; hybrid architecture}, issn = {1424-8220}, doi = {10.3390/s19081795}, url = {https://www.mdpi.com/1424-8220/19/8/1795}, author = {X. Lin and D. Sanchez-Escobedo and Casas, J. and M. Pard{\`a}s} } @article {aRoisman18, title = {Differential expression of long non-coding RNAs related to proliferation and histological diversity in follicular lymphomas}, journal = {British Journal of Haematology}, volume = {184}, year = {2019}, month = {Feb 2019}, pages = {373-383}, issn = {ISSN:1365-2141}, doi = {DOI: 10.1111/bjh.15656}, author = {A. Roisman and A. Navarro and G. Clot and G. Castellano and B. Gonzalez-Farre and P. P{\'e}rez-Galan and A. Esteve and M. Dabad and S. Heath and M. Gut and Bosio, M. and P. Bellot and Salembier, P. and Albert Oliveras and I. Slavusky and L. Magnano and H. Horn and A. Rosenwald and G. Ott and M. Aymerich and A. L{\'o}pez-Guillermo and P. Jares and J.I. Mart{\'\i}n-Subero and E. Campo and L. Hern{\'a}ndez} } @article {aGene-Molab, title = {Fruit Detection in an Apple Orchard Using a Mobile Terrestrial Laser Scanner}, journal = {Biosystems Engineering}, volume = {187}, year = {2019}, month = {09/2019}, chapter = {171}, abstract = {

The development of reliable fruit detection and localization systems provides an opportunity to improve the crop value and management by limiting fruit spoilage and optimized harvesting practices. Most proposed systems for fruit detection are based on RGB cameras and thus are affected by intrinsic constraints, such as variable lighting conditions. This work presents a new technique that uses a mobile terrestrial laser scanner (MTLS) to detect and localise Fuji apples. An experimental test focused on Fuji apple trees (Malus domestica Borkh. cv. Fuji) was carried out. A 3D point cloud of the scene was generated using an MTLS composed of a Velodyne VLP-16 LiDAR sensor synchronized with an RTK-GNSS satellite navigation receiver. A reflectance analysis of tree elements was performed, obtaining mean apparent reflectance values of 28.9\%, 29.1\%, and 44.3\% for leaves, branches and trunks, and apples, respectively. These results suggest that the apparent reflectance parameter (at 905 nm wavelength) can be useful to detect apples. For that purpose, a four-step fruit detection algorithm was developed. By applying this algorithm, a localization success of 87.5\%, an identification success of 82.4\%, and an F1-score of 0.858 were obtained in relation to the total amount of fruits. These detection rates are similar to those obtained by RGB-based systems, but with the additional advantages of providing direct 3D fruit location information, which is not affected by sunlight variations. From the experimental results, it can be concluded that LiDAR-based technology and, particularly, its reflectance information, has potential for remote apple detection and 3D location.

}, issn = {1537-5110}, doi = {10.1016/j.biosystemseng.2019.08.017}, url = {https://authors.elsevier.com/c/1Zmc45Tbkk9EHW}, author = {Gen{\'e}-Mola, Jordi and Gregorio, Eduard and Guevara, Javier and Auat Cheein, Fernando and Sanz, Ricardo and Escol{\`a}, Alexandre and Llorens Calveras, Jordi and Morros, J.R. and Ruiz-Hidalgo, J. and Ver{\'o}nica Vilaplana and Rosell-Polo, Joan R.} } @conference {cSalvadorf, title = {Inverse Cooking: Recipe Generation from Food Images}, booktitle = {CVPR}, year = {2019}, month = {06/2019}, publisher = {OpenCVF / IEEE}, organization = {OpenCVF / IEEE}, address = {Long Beach, CA, USA}, abstract = {

People enjoy food photography because they appreciate food. Behind each meal there is a story described in a complex recipe and, unfortunately, by simply looking at a food image we do not have access to its preparation process. Therefore, in this paper we introduce an inverse cooking system that recreates cooking recipes given food images. Our system predicts ingredients as sets by means of a novel architecture, modeling their dependencies without imposing any order, and then generates cooking instructions by attending to both image and its inferred ingredients simultaneously. We extensively evaluate the whole system on the large-scale Recipe1M dataset and show that (1) we improve performance w.r.t. previous baselines for ingredient prediction; (2) we are able to obtain high quality recipes by leveraging both image and ingredients; (3) our system is able to produce more compelling recipes than retrieval-based approaches according to human judgment.

}, url = {http://openaccess.thecvf.com/content_CVPR_2019/html/Salvador_Inverse_Cooking_Recipe_Generation_From_Food_Images_CVPR_2019_paper.html}, author = {Amaia Salvador and Drozdzal, Michal and Xavier Gir{\'o}-i-Nieto and Romero, Adriana} } @article {aSala, title = {Measuring traffic lane-changing by converting video into space-time still images}, journal = {Computer-Aided Civil and Infrastructure Engineering}, year = {2019}, month = {01/2019}, abstract = {

Empirical data is needed in order to extend\ our knowledge of traffic behavior. Video recordings are\ used to enrich typical data from loop detectors. In this\ context, data extraction from videos becomes a\ challenging task. Setting automatic video processing\ systems is costly, complex, and the accuracy achieved is\ usually not enough to improve traffic flow models. In\ contrast "visual" data extraction by watching the\ recordings requires extensive human intervention.

A semi-automatic video processing methodology to\ count lane-changing in freeways is proposed. The method\ allows counting lane changes faster than with the visual\ procedure without falling into the complexities and\ errors of full automation. The method consists in\ converting the video into a set of space-time still images,\ from where to visually count. This methodology has been\ tested at several freeway locations near Barcelona\ (Spain) with good results

}, doi = {https://doi.org/10.1111/mice.12430}, url = {https://onlinelibrary.wiley.com/doi/full/10.1111/mice.12430}, author = {Marcel Sala and Francesc Soriguera and Kevin Huillca and Ver{\'o}nica Vilaplana} } @article {xLLados19, title = {The pillars of the Computer Vision Catalan Alliance}, year = {2019}, abstract = {

Panel at the 6th Annual Catalan Meeting on Computer Vision.

$\#$ACM2019 @JosepLlados now introducing CVCatalliance with @xantallavina and experts from different sectors: @Vilynx @Satellogic @osalap @TheCollider_MWC @DocXavi pic.twitter.com/o5tVWW0gMQ

{\textemdash} CVC_UAB (@CVC_UAB) September 17, 2019
}, author = {LLad{\'o}s, Josep and Bou, Elisenda and Bressan, Marco and Sala, Oscar and Xavier Gir{\'o}-i-Nieto} } @conference {cPareto, title = {Prediction of a second clinical event in CIS patients by combining lesion and brain features}, booktitle = {Congress of the European Comitee for Treatment and Research in Multiple Sclerosis (ECTRIMS 2019)}, year = {2019}, month = {09/2019}, abstract = {

Prediction of a second clinical event in clinically isolated syndrome (CIS) patients, leading to clinically definite multiple sclerosis (CDMS), is still a matter of investigation. The aim of the current study was to predict conversion to CDMS after a first attack, by means of a machine-learning approach and MRI-derived brain features. For that purpose, lesion-based features (volume and distribution within brain lobes) as well as cortical thickness (CT) and deep grey matter volumes (DGMV) were used. The final goal was to determine which features were more frequently found in the classification between converters and non-converters.

}, author = {Deborah Pareto and Pau Vidal and M. Alberich and Carlos Lopez and C. Auger and M. Tintor{\'e} and X. Montalban and J. Sastre-Garriga and Ver{\'o}nica Vilaplana and Alex Rovira} } @conference {cSalembier19, title = {Processing Radar Images with Hierarchical Region-Based Representations and Graph Signal Processing Tools}, booktitle = {Workshop on Digital Topology and Mathematical Morphology associated to the 21st IAPR International Conference on Discrete Geometry for Computer Imagery, Keynote speech}, year = {2019}, address = {Paris, France}, author = {Salembier, P.} } @conference {cHerrera-Palacioa, title = {Recurrent Instance Segmentation using Sequences of Referring Expressions}, booktitle = {NeurIPS workshop on Visually Grounded Interaction and Language (ViGIL)}, year = {2019}, month = {09/2019}, address = {Vancouver, Canada}, abstract = {

The goal of this work is segmenting the objects in an image which are referred to by a sequence of linguistic descriptions (referring expressions). We propose a deep neural network with recurrent layers that output a sequence of binary masks, one for each referring expression provided by the user. The recurrent layers in the architecture allow the model to condition each predicted mask on the previous ones, from a spatial perspective within the same image. Our multimodal approach uses off-the-shelf architectures to encode both the image and the referring expressions. The visual branch provides a tensor of pixel embeddings that are concatenated with the phrase embeddings produced by a language encoder. Our experiments on the RefCOCO dataset for still images indicate how the proposed architecture successfully exploits the sequences of referring expressions to solve a pixel-wise task of instance segmentation.

Recurrent Instance Segmentation with Linguistic Referring Expressions from Universitat Polit{\`e}cnica de Catalunya
}, author = {Herrera-Palacio, Alba and Ventura, C. and Silberer, Carina and Sorodoc, Ionut-Teodor and Boleda, Gemma and Xavier Gir{\'o}-i-Nieto} } @mastersthesis {xHerrera-Palacio, title = {Recurrent Instance Segmentation with Linguistic Referring Expressions}, year = {2019}, abstract = {

The goal of this work is segmenting the object in an image or video which is referred to by a linguistic description (referring expression).\ We propose a deep neural network with recurrent layers that output a sequence of binary masks, one for each referring expression provided by the user.\ The recurrent layers in the architecture allow the model to condition each predicted mask on the previous ones, from a spatial perspective within the same image.\ Our multimodal approach uses off-the-shelf architectures to encode both the image and the referring expressions.\ The visual branch provides a tensor of pixel embeddings that are concatenated with the phrase embeddings produced by a language encoder.\ We focus our study on comparing different configurations to encode and combine the visual and linguistic representations.\ Our experiments on the RefCOCO dataset for still images indicate how the proposed architecture successfully exploits the referring expressions to solve a pixel-wise task of instance segmentation.

Recurrent Instance Segmentation with Linguistic Referring Expressions from Universitat Polit{\`e}cnica de Catalunya
}, author = {Herrera-Palacio, Alba}, editor = {Xavier Gir{\'o}-i-Nieto and Ventura, C. and Silberer, Carina} } @conference {cVenturaa, title = {RVOS: End-to-End Recurrent Network for Video Object Segmentation}, booktitle = {CVPR}, year = {2019}, month = {06/2019}, publisher = {OpenCVF / IEEE}, organization = {OpenCVF / IEEE}, address = {Long Beach, CA, USA}, abstract = {

Multiple object video object segmentation is a challenging task, specially for the zero-shot case, when no object mask is given at the initial frame and the model has to find the objects to be segmented along the sequence. In our work, we propose RVOS, a recurrent network that is fully end-to-end trainable for multiple object video object segmentation, with a recurrence module working on two different domains: (i) the spatial, which allows to discover the different object instances within a frame, and (ii) the temporal, which allows to keep the coherence of the segmented objects along time. We train RVOS for zero-shot video object segmentation and are the first ones to report quantitative results for DAVIS-2017 and YouTube-VOS benchmarks. Further, we adapt RVOS for one-shot video object segmentation by using the masks obtained in previous time-steps as inputs to be processed by the recurrent module. Our model reaches comparable results to state-of-the-art techniques in YouTube-VOS benchmark and outperforms all previous video object segmentation methods not using online learning in the DAVIS-2017 benchmark.

RVOS: End-to-End Recurrent Network for Video Object Segmentation (CVPR 2019) from Universitat Polit{\`e}cnica de Catalunya



}, url = {http://openaccess.thecvf.com/content_CVPR_2019/html/Ventura_RVOS_End-To-End_Recurrent_Network_for_Video_Object_Segmentation_CVPR_2019_paper.html}, author = {Ventura, C. and M{\'\i}riam Bellver and Girbau, A. and Amaia Salvador and Marqu{\'e}s, F. and Xavier Gir{\'o}-i-Nieto} } @article {aSalembier18, title = {Ship Detection in SAR Images Based on Maxtree Representation and Graph Signal Processing}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, volume = {57}, year = {2019}, month = {05/2019}, pages = {2709 - 2724}, author = {Salembier, P. and Liesegang, S. and L{\'o}pez-Mart{\'\i}nez, C.} } @article {aKuijf, title = {Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities; Results of the WMH Segmentation Challenge}, journal = {IEEE Transactions on Medical Imaging}, year = {2019}, month = {03/2019}, abstract = {

Quantification of white matter hyperintensities (WMH) of presumed vascular origin is of key\ importance in many neurological research studies. Advanced\ measurements are obtained from manual segmentations on brain\ MR images, which is a laborious procedure. Automatic WMH\ segmentation methods exist, but a standardized comparison of\ such methods is lacking. We organized a scientific challenge, in\ which developers could evaluate their method on a standardized\ multi-center/-scanner image dataset, giving an objective comparison:\ the WMH Segmentation Challenge (http://wmh.isi.uu.nl/).\ Sixty T1+FLAIR images from three MR scanners were released\ with manual WMH segmentations. A secret test set of 110\ images from five MR scanners was used for evaluation. Methods\ had to be containerized and submitted to the challenge organizers.Five evaluation metrics were used to rank the methods:\ (1) Dice Similarity Coefficient, (2) modified Hausdorff distance\ (95th percentile), (3) absolute percentage volume difference, (4)\ sensitivity for detecting individual lesions, and (5) F1-score for\ individual lesions. Additionally, methods were ranked on their\ inter-scanner robustness.\ Twenty participants submitted their method for evaluation.\ This paper provides a detailed analysis of the results. In brief,there is a cluster of four methods that rank significantly better\ than the other methods. There is one clear winner, which also\ has the best inter-scanner robustness.\ The challenge remains open for future submissions and provides\ a public platform for method evaluation.

}, keywords = {brain, Evaluation and performance, Magnetic resonance imaging (MRI), segmentation}, issn = {0278-0062}, doi = {10.1109/TMI.2019.2905770}, author = {Hugo Kuijf and Matthijs Biesbroek and Jeroen de Bresser and Rutger Heinen and Simon Andermatt and Mariana Bento and Matt Berseth and Mikhail Belyaev and Jorge Cardoso and Adri{\`a} Casamitjana and Louis Collins and Mahsa Dadar and Achileas Georgiou and Mohsen Ghafoorian and Dakai Jin and April Khademi and Jesse Knight and Hongwei Li and Xavier Llado and Miguel Luna and Qaiser Mahmood and Richard McKinley and Alireza Mehrtash and Sebastien Ourselin and Bo-yong Park and Hyunkin Park and Sang Hyun Park and Simon Pezold and Elodie Puybareau and Leticia Rittner and Carole Sudre and Sergi Valverde and Ver{\'o}nica Vilaplana and Rolan Wiest and Yongchao Xu and Ziyue Xu and Guodong Zeng and Jianguo Zhang and Guoyan Zheng and Christoper Chen and Wiesje van der Flier and Frederik Barkhof and Max Viergever and Geert Jan Biessels} } @inbook {bBellot19, title = {Unsupervised GRN Ensemble}, booktitle = {Sanguinetti G., Huynh-Thu V. (eds) Methods in Molecular Biology }, volume = {1883}, year = {2019}, pages = {283-302}, publisher = { Springer science, Humana Press}, organization = { Springer science, Humana Press}, address = {New York, NY}, issn = {978-1-4939-8881-5}, doi = {https://doi-org.recursos.biblioteca.upc.edu/10.1007/978-1-4939-8882-2}, author = {P. Bellot and Salembier, P. and Pham, N.C. and Meyer, P. E.} } @conference {cDuartea, title = {Wav2Pix: Speech-conditioned Face Generation using Generative Adversarial Networks}, booktitle = {ICASSP}, year = {2019}, month = {05/2019}, publisher = {IEEE}, organization = {IEEE}, address = {Brighton, UK}, abstract = {

Speech is a rich biometric signal that contains information\ about the identity, gender and emotional state of the speaker.\ In this work, we explore its potential to generate face images\ of a speaker by conditioning a Generative Adversarial\ Network (GAN) with raw speech input. We propose a deep\ neural network that is trained from scratch in an end-to-end\ fashion, generating a face directly from the raw speech waveform\ without any additional identity information (e.g reference\ image or one-hot encoding). Our model is trained in a\ self-supervised fashion by exploiting the audio and visual signals\ naturally aligned in videos. With the purpose of training\ from video data, we present a novel dataset collected for this\ work, with high-quality videos of ten youtubers with notable\ expressiveness in both the speech and visual signals.

}, doi = {10.1109/ICASSP.2019.8682970}, url = {http://hdl.handle.net/2117/167073}, author = {Amanda Duarte and Rold{\'a}n, Francisco and Tubau, Miquel and Escur, Janna and Pascual-deLaPuente, Santiago and Amaia Salvador and Mohedano, Eva and McGuinness, Kevin and Jordi Torres and Xavier Gir{\'o}-i-Nieto} } @inbook {bTochon18, title = {Advances in utilization of hierarchical representations in remote sensing data analysis}, booktitle = {Reference Module in Earth Systems and Environmental Sciences}, volume = {2}, year = {2018}, pages = {77-107}, publisher = {Elsevier}, organization = {Elsevier}, issn = {978-0-12-409548-9}, author = {G. Tochon and Dalla Mura, M. and Veganzones, M.A. and Valero, S. and Salembier, P. and Chanussot, J.} } @conference {cSancheza, title = {Brain MRI Super-Resolution using Generative Adversarial Networks}, booktitle = {International Conference on Medical Imaging with Deep Learning}, year = {2018}, month = {07/2018}, address = {Amsterdam, The Netherlands}, author = {Irina S{\'a}nchez and Ver{\'o}nica Vilaplana} } @inbook {bCasamitjana18, title = {Cascaded V-Net Using ROI Masks for Brain Tumor Segmentation}, booktitle = {Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2017}, volume = { 10670}, number = {Lecture Notes in Computer Science}, year = {2018}, pages = {381-391}, publisher = {Springer}, organization = {Springer}, edition = {Crimi A., Bakas S., Kuijf H., Menze B., Reyes M. (eds)}, address = {Cham}, abstract = {

In this work we approach the brain tumor segmentation problem with a cascade of two CNNs inspired in the V-Net architecture, reformulating residual connections and making use of ROI masks to constrain the networks to train only on relevant voxels. This architecture allows dense training on problems with highly skewed class distributions, such as brain tumor segmentation, by focusing training only on the vecinity of the tumor area. We report results on BraTS2017 Training and Validation sets.

}, isbn = {978-3-319-75238-9}, issn = {978-3-319-75237-2}, doi = {https://doi.org/10.1007/978-3-319-75238-9_33}, url = {https://link.springer.com/chapter/10.1007/978-3-319-75238-9_33}, author = {Adri{\`a} Casamitjana and Marcel Cat{\`a} and Irina S{\'a}nchez and Marc Combalia and Ver{\'o}nica Vilaplana} } @conference {cPetrone, title = {Characteristic Brain Volumetric Changes in the AD Preclinical Signature}, booktitle = {Alzheimer{\textquoteright}s Association International Conference}, year = {2018}, month = {07/2018}, address = {Chicago, USA}, abstract = {

In the last decade, magnetic resonance imaging has unveiled specific AD alterations at different stages of the AD pathophysiologic continuum that conform what has been established as the AD signature. To which extent MRI can detect structural changes at the preclinical asymptomatic stage of AD - the preclinical AD signature- is still an area open for exploration. Our work supports the idea that there are brain volumetric changes specific to preclinical AD subjects and defines the preclinical AD signature based on longitudinal data. While some regions show a pattern of atrophy that overlaps with the AD signature, other specific regions exhibit changes that are unique to this early asymptomatic AD stage.

}, author = {P. Petrone and Adri{\`a} Casamitjana and C. Falcon and M. Artigues and G. Operto and S. Skouras and R. Cacciaglia and J.L. Molinuevo and Ver{\'o}nica Vilaplana and J.D. Gispert} } @article {aPetrone18, title = {Characteristic Brain Volumetric Changes in the AD Preclinical Signature.}, journal = {Alzheimer{\textquoteright}s \& Dementia: The Journal of the Alzheimer{\textquoteright}s Association}, volume = {14}, year = {2018}, month = {07/2018}, pages = {P1235}, doi = {10.1016/j.jalz.2018.06.1737}, author = {P. Petrone and Adri{\`a} Casamitjana and C. Falcon and M. Artigues and G. Operto and S. Skouras and J.L. Molinuevo and Ver{\'o}nica Vilaplana and J.D. Gispert} } @conference {cSuris, title = {Cross-modal Embeddings for Video and Audio Retrieval}, booktitle = {ECCV 2018 Women in Computer Vision Workshop}, year = {2018}, month = {09/2018}, publisher = {Springer}, organization = {Springer}, address = {Munich, Germany}, abstract = {

The increasing amount of online videos brings several opportunities for training self-supervised neural networks. The creation of large scale datasets of videos such as the YouTube-8M allows us to deal with this large amount of data in manageable way. In this work, we find new ways of exploiting this dataset by taking advantage of the multi-modal information it provides. By means of a neural network, we are able to create links between audio and visual documents, by projecting them into a common region of the feature space, obtaining joint audio-visual embeddings. These links are used to retrieve audio samples that fit well to a given silent video, and also to retrieve images that match a given a query audio. The results in terms of Recall@K obtained over a subset of YouTube-8M videos show the potential of this unsupervised approach for cross-modal feature learning. We train embeddings for both scales and assess their quality in a retrieval problem, formulated as using the feature extracted from one modality to retrieve the most similar videos based on the features computed in the other modality.

Cross Modal Embeddings for Video and Audio Retrieval $\#$WiCV18 from Universitat Polit{\`e}cnica de Catalunya
}, isbn = {978-3-030-11018-5}, doi = {10.1007/978-3-030-11018-5_62}, url = {https://doi.org/10.1007/978-3-030-11018-5_62}, author = {Sur{\'\i}s, D{\'\i}dac and Amanda Duarte and Amaia Salvador and Jordi Torres and Xavier Gir{\'o}-i-Nieto} } @conference {cSanchez-Escobedo, title = {HybridNet for Depth Estimation and Semantic Segmentation}, booktitle = {ICASSP 2018}, year = {2018}, month = {04/2018}, publisher = {IEEE}, organization = {IEEE}, address = {Calgary, Alberta, Canada}, abstract = {

Semantic segmentation and depth estimation are two important tasks in the area of image processing. Traditionally, these two tasks are addressed in an independent manner. However, for those applications where geometric and semantic information is required, such as robotics or autonomous navigation, depth or semantic segmentation alone are not sufficient. In this paper, depth estimation and semantic segmentation are addressed together from a single input image through a hybrid convolutional network. Different from the state of the art methods where features are extracted by a sole feature extraction network for both tasks, the proposed HybridNet improves the features extraction by separating the relevant features for one task from those which are relevant for both. Experimental results demonstrate that HybridNet results are comparable with the state of the art methods, as well as the single task methods that HybridNet is based on.

}, doi = {10.1109/ICASSP.2018.8462433}, url = {https://ieeexplore.ieee.org/abstract/document/8462433}, author = {D. Sanchez-Escobedo and X. Lin and Casas, J. and M. Pard{\`a}s} } @conference {cGorrizb, title = {Leishmaniasis Parasite Segmentation and Classification Using Deep Learning}, booktitle = {International Conference on Articulated Motion and Deformable Objects}, year = {2018}, address = {Palma, Spain}, abstract = {

Leishmaniasis is considered a neglected disease that causes thousands of deaths annually in some tropical and subtropical countries. There are various techniques to diagnose leishmaniasis of which manual microscopy is considered to be the gold standard. There is a need for the development of automatic techniques that are able to detect parasites in a robust and unsupervised manner. In this paper we present a procedure for automatizing the detection process based on a deep learning approach. We train a U-net model that successfully segments leismania parasites and classifies them into promastigotes, amastigotes and adhered parasites.

}, author = {G{\'o}rriz, Marc and Albert Aparicio and Berta Ravent{\'o}s and Daniel L{\'o}pez-Codina and Ver{\'o}nica Vilaplana and Elisa Sayrol} } @inbook {bGorriz18, title = {Leishmaniasis Parasite Segmentation and Classification Using Deep Learning}, booktitle = { Articulated Motion and Deformable Objects}, volume = {10945}, number = {Lecture Notes in Computer Science}, year = {2018}, pages = {53-62}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, abstract = {

Leishmaniasis is considered a neglected disease that causes thousands of deaths annually in some tropical and subtropical countries. There are various techniques to diagnose leishmaniasis of which manual microscopy is considered to be the gold standard. There is a need for the development of automatic techniques that are able to detect parasites in a robust and unsupervised manner. In this paper we present a procedure for automatizing the detection process based on a deep learning approach. We train a U-net model that successfully segments leismania parasites and classifies them into promastigotes, amastigotes and adhered parasites.

}, issn = {978-3-319-94544-6}, doi = {10.1007/978-3-319-94544-6}, author = {G{\'o}rriz, Marc and Albert Aparicio and Berta Ravent{\'o}s and Ver{\'o}nica Vilaplana and Elisa Sayrol and Daniel L{\'o}pez-Codina} } @article {pPerez-Pellitero17, title = {Method for upscaling an image and apparatus for upscaling an image}, number = {US 20170132759 A1}, year = {2018}, month = {05/2017}, address = {US 20170132759 A1}, abstract = {

Image super-resolution (SR) generally enhance the resolution of images. One of SR{\textquoteright}s main challenge is discovering mappings between low-resolution (LR) and high-resolution (HR) image patches. The invention learns patch upscaling projection matrices from a training set of images. Input images are divided into overlapping patches, which are normalized and transformed to a defined orientation. Different transformations can be recognized and dealt with by using a simple 2D-projection. The transformed patches are clustered, and cluster specific upscaling projection matrices and corresponding cluster centroids determined during training are applied to obtain upscaled patches. The upscaled patches are assembled to an upscaled image.

https://worldwide.espacenet.com/publicationDetails/biblio?II=2\&ND=3\&adjacent=true\&locale=en_EP\&FT=D\&date=20170511\&CC=US\&NR=2017132759A1\&KC=A1

}, issn = {US 20170132759 A1}, url = {https://register.epo.org/ipfwretrieve?apn=US.201615341080.A\&lng=en}, author = {E. Perez-Pellitero and Salvador, J. and Ruiz-Hidalgo, J. and Rosenhahn, B.} } @article {aCasamitjana, title = {MRI-Based Screening of Preclinical Alzheimer{\textquoteright}s Disease for Prevention Clinical Trials}, journal = {Journal of Alzheimer{\textquoteright}s Disease}, volume = {64}, year = {2018}, month = {07/2018}, chapter = {1099}, abstract = {

The identification of healthy individuals harboring amyloid pathology constitutes one important challenge for secondary prevention clinical trials in Alzheimer{\textquoteright}s disease (AD). Consequently, noninvasive and cost-efficient techniques to detect preclinical AD constitute an unmet need of critical importance. In this manuscript, we apply machine learning to structural MRI (T1 and DTI) of 96 cognitively normal subjects to identify amyloid-positive ones. Models were trained on public ADNI data and validated on an independent local cohort. Used for subject classification in a simulated clinical trial setting, the proposed method is able to save 60\% unnecessary CSF/PET tests and to reduce 47\% of the cost of recruitment when used in a simulated clinical trial setting. This recruitment strategy capitalizes on already acquired MRIs to reduce the overall amount of invasive PET/CSF tests in prevention trials, demonstrating a potential value as a tool for AD screening. This protocol could foster the development of secondary prevention strategies for AD.

}, author = {Adri{\`a} Casamitjana and Paula Petrone and Alan Tucholka and Carles Falcon and Stavros Skouras and Jose Luis Molinuevo and Ver{\'o}nica Vilaplana and Juan D. Gispert} } @conference {cShou, title = {Online Action Detection in Untrimmed, Streaming Videos}, booktitle = {European Conference on Computer Vision (ECCV)}, year = {2018}, month = {02/2018}, address = {Munich, German}, abstract = {

}, url = {https://arxiv.org/abs/1802.06822}, author = {Shou, Zheng and Pan, Junting and Chan, Johnatan and Miyazawa, Kazuyuki and Mansour, Hassan and Vetro, Anthony and Xavier Gir{\'o}-i-Nieto and Chang, Shih-Fu} } @conference {cSalvadord, title = {Recurrent Neural Networks for Semantic Instance Segmentation}, booktitle = {ECCV 2018 Women in Computer Vision (WiCV) Workshop}, year = {2018}, month = {12/2017}, abstract = {

We present a recurrent model for semantic instance segmentation that sequentially generates pairs of masks and their associated class probabilities for every object in an image. Our proposed system is trainable end-to-end, does not require post-processing steps on its output and is conceptually simpler than current methods relying on object proposals. We observe that our model learns to follow a consistent pattern to generate object sequences, which correlates with the activations learned in the encoder part of our network. We achieve competitive results on three different instance segmentation benchmarks (Pascal VOC 2012, Cityscapes and CVPPP Plant Leaf Segmentation).

Recurrent Neural Networks for Semantic Instance Segmentation from Universitat Polit{\`e}cnica de Catalunya
}, url = {https://imatge-upc.github.io/rsis/}, author = {Amaia Salvador and M{\'\i}riam Bellver and Baradad, Manel and V{\'\i}ctor Campos and Marqu{\'e}s, F. and Jordi Torres and Xavier Gir{\'o}-i-Nieto} } @conference {cSalvadore, title = {Recurrent Neural Networks for Semantic Instance Segmentation}, booktitle = {CVPR 2018 DeepVision Workshop}, year = {2018}, month = {06/2018}, abstract = {

We present a recurrent model for semantic instance segmentation that sequentially generates binary masks and their associated class probabilities for every object in an image. Our proposed system is trainable end-to-end from an input image to a sequence of labeled masks and, compared to methods relying on object proposals, does not require post-processing steps on its output. We study the suitability of our recurrent model on three different instance segmentation benchmarks, namely Pascal VOC 2012, CVPPP Plant Leaf Segmentation and Cityscapes. Further, we analyze the object sorting patterns generated by our model and observe that it learns to follow a consistent pattern, which correlates with the activations learned in the encoder part of our network.

}, author = {Amaia Salvador and M{\'\i}riam Bellver and Baradad, Manel and V{\'\i}ctor Campos and Marqu{\'e}s, F. and Jordi Torres and Xavier Gir{\'o}-i-Nieto} } @mastersthesis {xRoldana, title = {Speech-conditioned Face Generation with Deep Adversarial Networks}, year = {2018}, abstract = {

Image synthesis have been a trending task for the AI community in recent years. Many works have shown the potential of Generative Adversarial Networks (GANs) to deal with tasks such as text or audio to image synthesis. In particular, recent advances in deep learning using audio have inspired many works involving both visual and auditory information. In this work we propose a face synthesis method using audio and/or language representations as inputs. Furthermore, a dataset which relates speech utterances with a face and an identity has been built, fitting for other tasks apart from face synthesis such as speaker recognition or voice conversion.

Speech Conditioned Face Generation with Deep Adversarial Networks from Universitat Polit{\`e}cnica de Catalunya
}, author = {Rold{\'a}n, Francisco}, editor = {Pascual-deLaPuente, Santiago and Amaia Salvador and McGuinness, Kevin and Xavier Gir{\'o}-i-Nieto} } @conference {cIndia18, title = {UPC Multimodal Speaker Diarization System for the 2018 Albayzin Challenge}, booktitle = {IberSpeech 2018}, year = {2018}, month = {11/2018}, address = {Barcelona}, abstract = {

This paper presents the UPC system proposed for the Multimodal Speaker Diarization task of the 2018 Albayzin Challenge. This approach works by processing individually the speech and the image signal. In the speech domain, speaker diarization is performed using identity embeddings created by a triplet loss DNN that uses i-vectors as input. The triplet DNN is trained with an additional regularization loss that minimizes the variance of both positive and negative distances. A sliding window is then used to compare speech segments with enrollment speaker targets using cosine distance between the embeddings. To detect identities from the face modality, a face detector followed by a face tracker has been used on the videos. For each cropped face a feature vector is obtained using a Deep Neural Network based on the ResNet 34 architecture, trained using a\  metric learning triplet loss (available from dlib library). For each track the face feature vector is obtained by averaging the features obtained for each one of the frames of that track. Then, this feature vector is compared with the features extracted from the images of the enrollment identities. The proposed system is evaluated on the RTVE2018 database.

}, keywords = {Face Diarization, Multimodal Systems, Speaker Diarization}, doi = {http://dx.doi.org/10.21437/IberSPEECH.2018-40}, author = {India, M. and Sagastiberri, I. and Palau, P. and Elisa Sayrol and Morros, J.R. and Hernando, J.} } @conference {cSanchez, title = {3D Medical Image Synthesis using Generative Adversarial Networks}, booktitle = {ACM Europe Celebration of Women in Computing, womENcourage 2017, Barcelona, Spain}, year = {2017}, month = {09/2017}, author = {Irina S{\'a}nchez and Ver{\'o}nica Vilaplana} } @article {xSalvador17, title = {Artificial intelligence suggests recipes based on food photos}, volume = {2017}, year = {2017}, publisher = {MIT News}, address = {Boston}, abstract = {

Given a still image of a dish filled with food, CSAIL team{\textquoteright}s deep-learning algorithm recommends ingredients and recipes.

}, url = {Artificial intelligence suggests recipes based on food photos}, author = {Amaia Salvador} } @conference {cCasamitjanaa, title = {Augmented V-Net for infant brain segmentation}, booktitle = {MICCAI Grand Challenge on 6-month Infant Brain MRI Segmentation, MICCAI 2017}, year = {2017}, month = {09/2017}, author = {Adri{\`a} Casamitjana and Irina S{\'a}nchez and Marc Combalia and Ver{\'o}nica Vilaplana} } @conference {cCasamitjana, title = {Augmented V-Net for White Matter Hyperintensities segmentation}, booktitle = {WMH Segmentation Challenge, Brain-lesion Workshop, MICCAI 2017 }, year = {2017}, month = {09/2017}, author = {Adri{\`a} Casamitjana and Irina S{\'a}nchez and Marc Combalia and Ver{\'o}nica Vilaplana} } @conference {cvan Sabben17, title = {Collaborative voting of 3D features for robust gesture estimation}, booktitle = {International Conference on Acoustics, Speech and Signal Processing}, year = {2017}, month = {03/2017}, address = {New Orleans, USA}, abstract = {

Human body analysis raises special interest because it enables a wide range of interactive applications. In this paper we present a gesture estimator that discriminates body poses in depth images. A novel collaborative method is proposed to learn 3D features of the human body and, later, to estimate specific gestures. The collaborative estimation framework is inspired by decision forests, where each selected point (anchor point) contributes to the estimation by casting votes. The main idea is to detect a body part by accumulating the inference of other trained body parts. The collaborative voting encodes the global context of human pose, while 3D features represent local appearance. Body parts contributing to the detection are interpreted as a voting process. Experimental results for different 3D features prove the validity of the proposed algorithm.

}, author = {van Sabben, D. and Ruiz-Hidalgo, J. and Suau, X. and Casas, J.} } @conference {c, title = {Distributed training strategies for a computer vision deep learning algorithm on a distributed GPU cluster}, booktitle = {International Conference on Computational Science (ICCS)}, year = {2017}, month = {06/2017}, publisher = {Elsevier}, organization = {Elsevier}, address = {Zurich, Switzerland}, abstract = {

Deep learning algorithms base their success on building high learning capacity models with millions of parameters that are tuned in a data-driven fashion. These models are trained by processing millions of examples, so that the development of more accurate algorithms is usually limited by the throughput of the computing devices on which they are trained. In this work, we explore how the training of a state-of-the-art neural network for computer vision can be parallelized on a distributed GPU cluster. The effect of distributing the training process is addressed from two different points of view. First, the scalability of the task and its performance in the distributed setting are analyzed. Second, the impact of distributed training methods on the final accuracy of the models is studied.

[ICCS 2017 website][Related session in ICCS 2017][Paper in UPCommons]

}, keywords = {distributed computing; parallel systems; deep learning; Convolutional Neural Networks}, doi = {https://doi.org/10.1016/j.procs.2017.05.074}, url = {http://www.sciencedirect.com/science/article/pii/S1877050917306129}, author = {V{\'\i}ctor Campos and Sastre, Francesc and Yag{\"u}es, Maurici and M{\'\i}riam Bellver and Xavier Gir{\'o}-i-Nieto and Jordi Torres} } @inbook {bBellot17, title = {Efficient Combination of Pairwise Feature Networks}, booktitle = {Neural Connectomics Challenge}, year = {2017}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, chapter = {7}, issn = {978-3-319-53069-7}, doi = {10.1007/978-3-319-53070-3}, author = {P Bellot and Patrick Meyer}, editor = {Battaglia, D and Guyon, I. and Lemaire, V. and Orlandi, J. and Ray, B. and Soriano, J.} } @conference {cSalvadorc, title = {Learning Cross-modal Embeddings for Cooking Recipes and Food Images}, booktitle = {CVPR}, year = {2017}, month = {03/2017}, publisher = {CVF / IEEE}, organization = {CVF / IEEE}, address = {Honolulu, Hawaii, USA}, abstract = {

In this paper, we introduce Recipe1M, a new large-scale, structured corpus of over 1m cooking recipes and 800k food images. As the largest publicly available collection of recipe data, Recipe1M affords the ability to train high-capacity models on aligned, multi-modal data. Using these data, we train a neural network to find a joint embedding of recipes and images that yields impressive results on an image-recipe retrieval task. Additionally, we demonstrate that regularization via the addition of a high-level classification objective both improves retrieval performance to rival that of humans and enables semantic vector arithmetic. We postulate that these embeddings will provide a basis for further exploration of the Recipe1M dataset and food and cooking in general.

[Project page]

In the news:

}, doi = {10.1109/CVPR.2017.327}, url = {http://openaccess.thecvf.com/content_cvpr_2017/html/Salvador_Learning_Cross-Modal_Embeddings_CVPR_2017_paper.html}, author = {Amaia Salvador and Hynes, Nicholas and Aytar, Yusuf and Marin, Javier and Ofli, Ferda and Weber, Ingmar and Torralba, Antonio} } @article {aPetrone17, title = {Magnetic Resonance Imaging as a valuable tool for Alzheimer{\textquoteright}s disease screening}, journal = {Alzheimer{\textquoteright}s \& Dementia: The Journal of the Alzheimer{\textquoteright}s Association}, volume = {13}, year = {2017}, month = {07/2017}, pages = {P1245}, doi = {10.1016/j.jalz.2017.07.457}, url = {https://doi.org/10.1016/j.jalz.2017.07.457}, author = {P. Petrone and Ver{\'o}nica Vilaplana and Adri{\`a} Casamitjana and D. Sanchez-Escobedo and A. Tucholka and R. Cacciaglia and G. Operto and S. Skouras and C. Falcon and J.L. Molinuevo and J.D. Gispert} } @conference {cPetrone17, title = {Magnetic Resonance Imaging as a valuable tool for Alzheimer{\textquoteright}s disease screening}, booktitle = {Alzheimer{\textquoteright}s Association International Conference, London, 2017}, year = {2017}, month = {07/2017}, author = {P. Petrone and Ver{\'o}nica Vilaplana and Adri{\`a} Casamitjana and A. Tucholka and C. Falcon and R. Cacciaglia and G. Operto and S. Skouras and J.L. Molinuevo and J.D. Gispert} } @conference {cCata, title = {Masked V-Net: an approach to brain tumor segmentation}, booktitle = {Multimodal Brain Tumor Segmentation Benchmark, Brain-lesion Workshop, MICCAI 2017 }, year = {2017}, month = {09/2017}, author = {Marcel Cat{\`a} and Adri{\`a} Casamitjana and Irina S{\'a}nchez and Marc Combalia and Ver{\'o}nica Vilaplana} } @article {xSalvador17b, title = {MIT is building a system that can identify a recipe using pictures of food}, year = {2017}, publisher = {Techcrunch}, abstract = {

Mastering the ability to distinguish hot dogs from not hot dogs is truly one of mankind{\textquoteright}s greatest achievements. Attempting to one-up that sort of masterstroke would surely be flying too close to the sun {\textemdash} but researchers at MIT are trying nonetheless.

}, url = {https://techcrunch.com/2017/07/20/mit-is-building-a-system-that-can-identify-a-recipe-using-pictures-of-food/}, author = {Amaia Salvador} } @inbook {bMohedano17, title = {Object Retrieval with Deep Convolutional Features}, booktitle = {Deep Learning for Image Processing Applications}, volume = {31}, number = {Advances in Parallel Computing}, year = {2017}, publisher = {IOS Press}, organization = {IOS Press}, address = {Amsterdam, The Netherlands}, abstract = {

Image representations extracted from convolutional neural networks (CNNs) outdo hand-crafted features in several computer vision tasks, such as visual image retrieval. This chapter recommends a simple pipeline for encoding the local activations of a convolutional layer of a pretrained CNN utilizing the well-known Bag of Words (BoW) aggregation scheme and called bag of local convolutional features (BLCF). Matching each local array of activations in a convolutional layer to a visual word results in an assignment map, which is a compact representation relating regions of an image with a visual word. We use the assignment map for fast spatial reranking, finding object localizations that are used for query expansion. We show the suitability of the BoW representation based on local CNN features for image retrieval, attaining state-of-the-art performance on the Oxford and Paris buildings benchmarks. We demonstrate that the BLCF system outperforms the latest procedures using sum pooling for a subgroup of the challenging TRECVid INS benchmark according to the mean Average Precision (mAP) metric.

}, issn = {978-1-61499-822-8 }, doi = {10.3233/978-1-61499-822-8-137}, url = {http://ebooks.iospress.nl/volumearticle/48028}, author = {Mohedano, Eva and Amaia Salvador and McGuinness, Kevin and Xavier Gir{\'o}-i-Nieto and O{\textquoteright}Connor, N. and Marqu{\'e}s, F.} } @conference {xSalvadora, title = {Recurrent Semantic Instance Segmentation}, booktitle = {NIPS 2017 Women in Machine Learning Workshop (WiML)}, year = {2017}, month = {12/2017}, publisher = {NIPS 2017 Women in Machine Learning Workshop}, organization = {NIPS 2017 Women in Machine Learning Workshop}, address = {Long Beach, CA, USA}, abstract = {

We present a recurrent model for end-to-end instance-aware semantic segmentation that is able to sequentially generate pairs of masks and class predictions. Our proposed system is trainable end-to-end for instance segmentation, does not require further post-processing steps on its output and is conceptually simpler than current methods relying on object proposals. While recent works have proposed recurrent architectures for instance segmentation, these are trained and evaluated for a single category.

Our model is composed of a series of Convolutional LSTMs that are applied in chain with upsampling layers in between to predict a sequence of binary masks and associated class probabilities. Skip connections are incorporated in our model by concatenating the output of the corresponding convolutional layer in the base model with the upsampled output of the ConvLSTM. Binary masks are finally obtained with a 1x1 convolution with sigmoid activation. We concatenate the side outputs of all ConvLSTM layers and apply a per-channel max-pooling operation followed by a single fully-connected layer with softmax activation to obtain the category for each predicted mask.

We train and evaluate our models with the Pascal VOC 2012 dataset. Future work will aim at analyzing and understanding the behavior of the network on other datasets, comparing the system with state of the art solutions and study the relationship of the learned object discovery patterns of our model with those of humans.

}, author = {Amaia Salvador and Baradad, Manel and Xavier Gir{\'o}-i-Nieto and Marqu{\'e}s, F.} } @conference {cPana, title = {SalGAN: Visual Saliency Prediction with Generative Adversarial Networks}, booktitle = {CVPR 2017 Scene Understanding Workshop (SUNw)}, year = {2017}, address = {Honolulu, Hawaii, USA}, abstract = {

We introduce SalGAN, a deep convolutional neural network for visual saliency prediction trained with adversarial examples. The first stage of the network consists of a generator model whose weights are learned by back-propagation computed from a binary cross entropy (BCE) loss over downsampled versions of the saliency maps. The resulting prediction is processed by a discriminator network trained to solve a binary classification task between the saliency maps generated by the generative stage and the ground truth ones. Our experiments show how adversarial training allows reaching state-of-the-art performance across different metrics when combined with a widely-used loss function like BCE.

}, url = {https://arxiv.org/abs/1701.01081}, author = {Pan, Junting and Cristian Canton-Ferrer and McGuinness, Kevin and O{\textquoteright}Connor, N. and Jordi Torres and Elisa Sayrol and Xavier Gir{\'o}-i-Nieto} } @conference {cTorres, title = {Scaling a Convolutional Neural Network for classification of Adjective Noun Pairs with TensorFlow on GPU Clusters}, booktitle = {17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)}, year = {2017}, month = {05/2017}, publisher = {IEEE}, organization = {IEEE}, address = {Madrid, Spain}, abstract = {

Deep neural networks have gained popularity in recent years, obtaining outstanding results in a wide range of applications such as computer vision in both academia and multiple industry areas. The progress made in recent years cannot be understood without taking into account the technological advancements seen in key domains such as High Performance Computing, more specifically in the Graphic Processing Unit (GPU) domain. These kind of deep neural networks need massive amounts of data to effectively train the millions of parameters they contain, and this training can take up to days or weeks depending on the computer hardware we are using. In this work, we present how the training of a deep neural network can be parallelized on a distributed GPU cluster. The effect of distributing the training process is addressed from two different points of view. First, the scalability of the task and its performance in the distributed setting are analyzed. Second, the impact of distributed training methods on the training times and final accuracy of the models is studied. We used TensorFlow on top of the GPU cluster of servers with 2 K80 GPU cards, at Barcelona Supercomputing Center (BSC). The results show an improvement for both focused areas. On one hand, the experiments show promising results in order to train a neural network faster. The training time is decreased from 106 hours to 16 hours in our experiments. On the other hand we can observe how increasing the numbers of GPUs in one node rises the throughput, images per second, in a near-linear way. Morever an additional distributed speedup of 10.3 is achieved with 16 nodes taking as baseline the speedup of one node.

[CCGRID 2017] [Paper page]

}, url = {http://easychair.org/smart-program/CCGRID2017/2017-05-15.html$\#$session:13550}, author = {Jordi Torres and Sastre, Francesc and Yag{\"u}es, Maurici and V{\'\i}ctor Campos and Xavier Gir{\'o}-i-Nieto} } @article {xSalvador17a, title = {Snap a photo, get a recipe: pic2recipe uses AI to predict food ingredients}, year = {2017}, publisher = {Digital Trends}, abstract = {

No recipe, no problem. Using image recognition, we can now learn how to cook something just by analyzing a photo.

}, url = {https://www.digitaltrends.com/photography/pics2recipe-mit-research/}, author = {Amaia Salvador} } @phdthesis {dBellot17, title = {Study of Gene Regulatory Networks Inference Methods from Gene Expression Data}, year = {2017}, author = {Pau Bellot}, editor = {Salembier, P.} } @conference {xDuarte, title = {Temporal-aware Cross-modal Embeddings for Video and Audio Retrieval}, booktitle = {NIPS 2017 Women in Machine Learning Workshop (WiML)}, year = {2017}, month = {12/2017}, publisher = {NIPS 2017 Women in Machine Learning Workshop}, organization = {NIPS 2017 Women in Machine Learning Workshop}, address = {Long Beach, CA, USA}, abstract = {

The increasing amount of videos online brings several opportunities for training self-supervised neural networks. In this work, we explore cross-modal embeddings between audio and vision by exploiting their alignment on YouTube videos.

Joint audio-visual embeddings allow creating links between audio and visual documents by projecting them to a common region of the feature space. They can be applied to enriching radio broadcasts with images, finding soundtracks for user-generated videos or simply enriching a topic search with both audio and video documents.

The idea of creating a joint embedding space across modalities has being exploited by other areas [3, 4]. However, joint representation between the video frames and its audio have yet to be fully exploited. A similar approach to the proposed one was [2], where a soundtrack was retrieved to match a music video. However, this work did not target a synchronization between both modalities.

We aim at training a temporal-aware embedding which can align both audio and visual tracks. We use the visual and audio features provided in the YouTube-8M dataset [1]. The dataset includes features at both the clip and frame (temporal window) level. We train embeddings for both scales and assess their quality in a retrieval problem, formulated as using the feature extracted from one modality to retrieve the most similar videos based on the features computed in the other modality.

We aim at not only finding related documents, but synchronize both sequences. The alignment between the two sequences will rely on computing temporal-aware features with recurrent neural networks at different scales. At retrieval time, different scales will be assessed and results evaluated both with ranking metrics and Amazon Mechanical Turk.

References

[1] Sami Abu-El-Haija, Nisarg Kothari, Joonseok Lee, Paul Natsev, George Toderici, Balakrishnan Varadarajan, and Sudheendra Vijayanarasimhan. Youtube-8m: A large-scale video classification benchmark. arXiv preprint arXiv:1609.08675, 2016.

[2] Sungeun Hong, Woobin Im, and Hyun S Yang. Deep learning for content-based, cross-modal retrieval of videos and music. arXiv preprint arXiv:1704.06761, 2017.

[3] Amaia Salvador, Nicholas Hynes, Yusuf Aytar, Javier Marin, Ferda Ofli, Ingmar Weber, and Antonio Torralba. Learning cross-modal embeddings for cooking recipes and food images. In CVPR, 2017.

[4] Liwei Wang, Yin Li, and Svetlana Lazebnik. Learning deep structure-preserving image-text embeddings. In CVPR, 2016.

}, author = {Amanda Duarte and Sur{\'\i}s, D{\'\i}dac and Amaia Salvador and Jordi Torres and Xavier Gir{\'o}-i-Nieto} } @conference {cLe, title = {Towards large scale multimedia indexing: A case study on person discovery in broadcast news}, booktitle = {International Workshop on Content-Based Multimedia Indexing - CBMI 2017}, year = {2017}, month = {06/2017}, address = {Firenze, Italy}, abstract = {

The rapid growth of multimedia databases and the human interest in their peers make indices representing the location and identity of people in audio-visual documents essential for searching archives. Person discovery in the absence of prior identity knowledge requires accurate association of audio-visual cues and detected names. To this end, we present 3 different strategies to approach this problem: clustering-based naming, verification-based naming, and graph-based naming. Each of these strategies utilizes different recent advances in unsupervised face / speech representation, verification, and optimization. To have a better understanding of the approaches, this paper also provides a quantitative and qualitative comparative study of these approaches using the associated corpus of the Person Discovery challenge at MediaEval 2016. From the results of our experiments, we can observe the pros and cons of each approach, thus paving the way for future promising research directions.

}, doi = {https://doi.org/10.1145/3095713.3095732}, author = {Nam Le and Herv{\'e} Bredin and Gabriel Sargent and Miquel India and Paula Lopez-Otero and Claude Barras and Camille Guinaudeau and Guillaume Gravier and Gabriel Barbosa da Fonseca and Izabela Lyon Freire and Zenilton Patroc{\'\i}nio Jr. and Silvio Jamil F. Guimaraes and Gerard Mart{\'\i} and Morros, J.R. and Javier Hernando and Laura Docio-Fernandez and Carmen Garcia-Mateo and Sylvain Meignier and Jean-Marc Odobez} } @conference {cCasamitjana16, title = {3D Convolutional Neural Networks for Brain Tumor Segmentation}, booktitle = {MICCAI 2016 - Brain Lesion Workshop (BrainLes), Multimodal Brain Tumor Segmentation Challenge (BRATS)}, year = {2016}, month = {11/2016}, author = {Adri{\`a} Casamitjana and Santi Puch and Asier Aduriz and Elisa Sayrol and Ver{\'o}nica Vilaplana} } @article {aPerez-Pellitero16, title = {Antipodally Invariant Metrics For Fast Regression-Based Super-Resolution}, journal = {IEEE Transactions on Image Processing}, volume = {25}, year = {2016}, month = {06/2016}, pages = {2468}, chapter = {2456}, abstract = {

Dictionary-based Super-Resolution algorithms usually select dictionary atoms based on distance or similarity metrics. Although the optimal selection of nearest neighbors is of central importance for such methods, the impact of using proper metrics for Super-Resolution (SR) has been overlooked in literature, mainly due to the vast usage of Euclidean distance. In this paper we present a very fast regression-based algorithm which builds on densely populated anchored neighborhoods and sublinear search structures. We perform a study of the nature of the features commonly used for SR, observing that those features usually lie in the unitary hypersphere, where every point has a diametrically opposite one, i.e. its antipode, with same module and angle, but opposite direction. Even though we validate the benefits of using antipodally invariant metrics, most of the binary splits use Euclidean distance, which does not handle antipodes optimally. In order to benefit from both worlds, we propose a simple yet effective Antipodally Invariant Transform (AIT) that can be easily included in the Euclidean distance calculation. We modify the original Spherical Hashing algorithm with this metric in our Antipodally Invariant Spherical Hashing scheme, obtaining the same performance as a pure antipodally invariant metric. We round up our contributions with a novel feature transform that obtains a better coarse approximation of the input image thanks to Iterative Back Projection. The performance of our method, which we named Antipodally Invariant Super-Resolution (AIS), improves quality (PSNR) and it is faster than any other state-of-the-art method.

}, doi = {10.1109/TIP.2016.2549362}, url = {http://perezpellitero.github.io/project_websites/ais_sr.html}, author = {E. Perez-Pellitero and Salvador, J. and Ruiz-Hidalgo, J. and Rosenhahn, B.} } @article {a, title = {Assessment of Crowdsourcing and Gamification Loss in User-Assisted Object Segmentation}, journal = {Multimedia Tools and Applications}, volume = {23}, year = {2016}, month = {11/2016}, chapter = {15901-15928}, abstract = {

There has been a growing interest in applying human computation -- \ particularly crowdsourcing techniques -- to assist in the solution of multimedia, image processing, and computer vision problems which are still too difficult to solve using fully automatic algorithms, and yet relatively easy for humans.

In this paper we focus on a specific problem -- object segmentation within color images -- and compare different solutions which combine color image segmentation algorithms with human efforts, either in the form of an explicit interactive segmentation task or through an implicit collection of valuable human traces with a game.\ We use Click{\textquoteright}n{\textquoteright}Cut, a friendly, web-based, interactive segmentation tool that allows segmentation tasks to be assigned to many users, and Ask{\textquoteright}nSeek, a game with a purpose designed for object detection and segmentation.

The two main contributions of this paper are: (i) We use the results of Click{\textquoteright}n{\textquoteright}Cut campaigns with different groups of users to examine and quantify the crowdsourcing loss incurred when an interactive segmentation task is assigned to paid crowd-workers, comparing their results to the ones obtained when computer vision experts are asked to perform the same tasks. (ii) Since interactive segmentation tasks are inherently tedious and prone to fatigue, we\ compare the quality \ of the results obtained with Click{\textquoteright}n{\textquoteright}Cut with the ones obtained using a (fun, interactive, and potentially less tedious) game designed for the same purpose. We call this contribution the assessment of the gamification loss, since it refers to how much quality of segmentation results may be lost when we switch to a game-based approach to the same task.\ 

We demonstrate that the crowdsourcing loss is significant when using all the data points from workers, but decreases substantially (and becomes comparable to the quality of expert users performing similar tasks) after performing a modest amount of data analysis and filtering out of users whose data are clearly not useful. We also show that -- on the other hand -- the gamification loss is significantly more severe: the quality of the results drops roughly by half when switching from a focused (yet tedious) task to a more fun and relaxed game environment.\ 

}, keywords = {Crowdsourcing, GWAP, Object detection, Object segmentation, Serious games}, issn = {1573-7721}, doi = {10.1007/s11042-015-2897-6}, url = {http://dx.doi.org/10.1007/s11042-015-2897-6}, author = {Carlier, Axel and Amaia Salvador and Cabezas, Ferran and Xavier Gir{\'o}-i-Nieto and Charvillat, Vincent and Marques, Oge} } @conference {cMohedanoa, title = {Bags of Local Convolutional Features for Scalable Instance Search}, booktitle = {ACM International Conference on Multimedia Retrieval (ICMR)}, year = {2016}, month = {06/2016}, publisher = {ACM}, organization = {ACM}, address = {New York City, NY; USA}, abstract = {

Image representations extracted from convolutional neural networks (CNNs) have been shown to outperform hand-crafted features in multiple computer vision tasks, such as visual image retrieval. This work proposes a simple pipeline for encoding the local activations of a convolutional layer of a pre-trained CNN using the well-known bag of words aggregation scheme (BoW). Assigning each local array of activations in a convolutional layer to a visual word produces an \textit{assignment map}, a compact representation that relates regions of an image with a visual word. We use the assignment map for fast spatial reranking, obtaining object localizations that are used for query expansion. We demonstrate the suitability of the Bag of Words representation based on local CNN features for image retrieval, achieving state-of-the-art performance on the Oxford and Paris buildings benchmarks. We show that our proposed system for CNN feature aggregation with BoW outperforms state-of-the-art techniques using sum pooling at a subset of the challenging TRECVid INS benchmark.

Best poster award at ACM ICMR 2016

Preprint on arXiv

Project page with source code

Post on GitXiv

Overall acceptance rate in ICMR 2016: 30\%\ 

2016-05-Seminar-AmaiaSalvador-DeepVision from Image Processing Group on Vimeo.

Convolutional Features for Instance Search from Xavier Giro
}, keywords = {Bag of Words, Convolutional Neural Networks, Instance Retrieval}, isbn = {978-1-4503-4359-6}, doi = {http://dx.doi.org/10.1145/2911996.2912061}, url = {http://dx.doi.org/10.1145/2911996.2912061}, author = {Mohedano, Eva and Amaia Salvador and McGuinness, Kevin and Xavier Gir{\'o}-i-Nieto and O{\textquoteright}Connor, N. and Marqu{\'e}s, F.} } @conference {cPoignant16, title = {The CAMOMILE Collaborative Annotation Platform for Multi-modal, Multi-lingual and Multi-media Documents}, booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)}, year = {2016}, month = {05/2016}, address = {Portoro{\v z} (Slovenia)}, abstract = {

In this paper, we describe the organization and the implementation of the CAMOMILE collaborative annotation framework for multimodal, multimedia, multilingual (3M) data. Given the versatile nature of the analysis which can be performed on 3M data, the structure of the server was kept intentionally simple in order to preserve its genericity, relying on standard Web technologies. Layers of annotations, defined as data associated to a media fragment from the corpus, are stored in a database and can be managed through standard interfaces with authentication. Interfaces tailored specifically to the needed task can then be developed in an agile way, relying on simple but reliable services for the management of the centralized annotations. We then present our implementation of an active learning scenario for person annotation in video, relying on the CAMOMILE server; during a dry run experiment, the manual annotation of 716 speech segments was thus propagated to 3504 labeled tracks. The code of the CAMOMILE framework is distributed in open source.

}, keywords = {active learning, Annotation tool, collaborative annotation, multimedia, person annotation}, isbn = {978-2-9517408-9-1}, url = {http://www.lrec-conf.org/proceedings/lrec2016/pdf/456_Paper.pdf}, author = {Johann Poignant and Mateusz Budnik and Herv{\'e} Bredin and Claude Barras and Mickael Stefas and Pierrick Bruneau and Gilles Adda and Laurent Besacier and Hazim Ekenel and Gil Francopoulo and Javier Hernando and Joseph Mariani and Morros, J.R. and Georges Qu{\'e}not and Sophie Rosset and Thomas Tamisier} } @conference {cMarsden, title = {Dublin City University and Partners{\textquoteright} Participation in the INS and VTT Tracks at TRECVid 2016}, booktitle = {TRECVID Workshop 2016}, year = {2016}, month = {11/2016}, address = {Gaithersburg, MD, USA}, abstract = {

DCU participated with a consortium of colleagues from NUIG and UPC in two tasks,\ INS and VTT. For the INS task we developed a framework consisting of face detection and\ representation and place detection and representation, with a user annotation of top-ranked\ videos. For the VTT task we ran 1,000 concept detectors from the VGG-16 deep CNN on\ 10 keyframes per video and submitted 4 runs for caption re-ranking, based on BM25, Fusion,\ Word2Vec and a fusion of baseline BM25 and Word2Vec. With the same pre-processing for\ caption generation we used an open source image-to-caption CNN-RNN toolkit NeuralTalk2\ to generate a caption for each keyframe and combine them.

}, url = {http://doras.dcu.ie/21484/}, author = {Marsden, Mark and Mohedano, Eva and McGuinness, Kevin and Calafell, Andrea and Xavier Gir{\'o}-i-Nieto and O{\textquoteright}Connor, N. and Zhou, Jiang and Azevedo, Lucas and Daubert, Tobias and Davis, Brian and H{\"u}rlimann, Manuela and Afli, Haithem and Du, Jinhua and Ganguly, Debasis and Li, Wei and Way, Andy and Smeaton, Alan F.} } @conference {cSalvadorb, title = {Faster R-CNN Features for Instance Search}, booktitle = {CVPR Workshop Deep Vision}, year = {2016}, month = {06/2016}, abstract = {

Image representations derived from pre-trained Convolutional Neural Networks (CNNs) have become the new state of the art in computer vision tasks such as instance retrieval. This work explores the suitability for instance retrieval of image- and region-wise representations pooled from an object detection CNN such as Faster R-CNN. We take advantage of the object proposals learned by a Region Proposal Network (RPN) and their associated CNN features to build an instance search pipeline composed of a first filtering stage followed by a spatial reranking. We further investigate the suitability of Faster R-CNN features when the network is fine-tuned for the same objects one wants to retrieve. We assess the performance of our proposed system with the Oxford Buildings 5k, Paris Buildings 6k and a subset of TRECVid Instance Search 2013, achieving competitive results.

2016-05-Seminar-AmaiaSalvador-DeepVision from Image Processing Group on Vimeo.

Convolutional Features for Instance Search from Xavier Giro
}, url = {http://www.cv-foundation.org/openaccess/content_cvpr_2016_workshops/w12/papers/Salvador_Faster_R-CNN_Features_CVPR_2016_paper.pdf}, author = {Amaia Salvador and Xavier Gir{\'o}-i-Nieto and Marqu{\'e}s, F. and Satoh, Shin{\textquoteright}ichi} } @conference {cPerez-Pellitero16, title = {Half Hypersphere Confinement for Piecewise Linear Regression}, booktitle = {IEEE Winter Conference on Applications of Computer Vision}, year = {2016}, month = {03/2016}, address = {Lake Placid, NY, USA}, abstract = {

2016 WACV\  \  \ 

IIn this paper we study the characteristics of the metrics best suited for the piecewise regression algorithms, in which comparisons are usually made between normalized vectors that lie on the unitary hypersphere. Even though Euclidean distance has been widely used for this purpose, it is suboptimal since it does not handle antipodal points (i.e. diametrically opposite points) properly. Therefore, we propose the usage of antipodally invariant metrics and introduce the Half Hypersphere Confinement (HHC), a fast alternative to Multidimensional Scaling (MDS) that allows to map antipodally invariant distances in the Euclidean space with very little approximation error. The performance of our method, which we named HHC Regression (HHCR), applied to Super-Resolution (SR) improves both in quality (PSNR) and it is faster than any other state-of-the-art method. Additionally, under an application-agnostic interpretation of our regression framework, we also test our algorithm for denoising and depth upscaling with promising results.

}, doi = {10.1109/WACV.2016.7477651}, author = {E. Perez-Pellitero and Salvador, J. and Ruiz-Hidalgo, J. and Rosenhahn, B.} } @conference {cGurrin, title = {LTA 2016 - The First Workshop on Lifelogging Tools and Applications}, booktitle = {ACM Multimedia}, year = {2016}, month = {10/2016}, publisher = {ACM}, organization = {ACM}, address = {Amsterdam, The Netherlands}, abstract = {

The organisation of personal data is receiving increasing research attention due to the challenges that are faced in gathering, enriching, searching and visualising this data. Given the increasing quantities of personal data being gathered by individuals, the concept of a lifelog digital library of rich multimedia and sensory content for every individual is fast becoming a reality. The LTA2016 lifelogging workshop at ACM MM 2016 aims to bring together academics and practitioners to discuss approaches to lifelog data analytics and the applications of same, and to debate the opportunities and challenges for researchers in this new and challenging area.

[Workshop web page]

[Workshop proceedings]

[UPCommons]

}, keywords = {lifelogging, Personal digital archives, Personal information management}, doi = {http://dx.doi.org/10.1145/2964284.2980534}, url = {http://lta2016.computing.dcu.ie/}, author = {Gurrin, Cathal and Xavier Gir{\'o}-i-Nieto and Radeva, Petia and Dimiccoli, M. and Johansen, H. and Joho, H. and Singh, Vivek K} } @mastersthesis {xSantamarta16, title = {Machine learning for recommendation systems in job postings selection}, year = {2016}, abstract = {

This project is the result of the study, implementation and combination of several recommender systems technics. Moreover, the project try to submit a solution for a challenge on job recommender system. Thus, it has been realized a study of the available technics on recommender systems. After that, it has been analyzed the information provided by organizers, in order to design the most accurate system. The design and the implementation of recommender systems models has been the next step on the project. Finally, the analysis and discussion of the results obtained has been the final step of the project. This step provides the best recommender system designed.

}, author = {Victor Marcos Santamarta}, editor = {Vidal, J. and Ver{\'o}nica Vilaplana} } @mastersthesis {xFerri16, title = {Object Tracking in Video with TensorFlow}, year = {2016}, abstract = {

[Project repo]

[Additional repo for setting up the environment]

}, author = {Ferri, Andrea}, editor = {Xavier Gir{\'o}-i-Nieto and Jordi Torres and Amaia Salvador} } @article {aSalembier, title = {Optimum Graph-Cuts for Pruning Binary Partition Trees of Polarimetric SAR images}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, volume = {54}, year = {2016}, month = {05/2016}, pages = {5493 {\textendash} 5502}, abstract = {

This paper investigates several optimum graph-cuts techniques for pruning Binary Partition Trees (BPTs) and their usefulness for low-level processing of Polarimetric SAR (PolSAR) images. BPTs group pixels to form homogeneous regions, which are hierarchically structured by inclusion in a binary tree. They provide multiple resolutions of description and easy access to subsets of regions. Once constructed, BPTs can be used for a large number of applications. Many of these applications consist in populating the tree with a specific feature and in applying a graph-cut called pruning to extract a partition of the space. In this paper, different pruning examples involving the optimization of a global criterion are discussed and analyzed in the context of PolSAR images for segmentation. Through objective evaluation of the resulting partitions by means of Precision and Recall for boundaries curves, the best pruning technique is identified and the influence of the tree construction on the performances is assessed.\ 

}, author = {Salembier, P. and S. Foucher} } @conference {cPerez-Pellitero, title = {PSyCo: Manifold Span Reduction for Super Resolution}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition}, year = {2016}, month = {06/2016}, address = {Las Vegas, Nevada, USA}, abstract = {

The main challenge in Super Resolution (SR) is to discover the mapping between the low- and high-resolution manifolds of image patches, a complex ill-posed problem which has recently been addressed through piecewise linear regression with promising results. In this paper we present a novel regression-based SR algorithm that benefits from an extended knowledge of the structure of both manifolds. We propose a transform that collapses the 16 variations induced from the dihedral group of transforms (i.e. rotations, vertical and horizontal reflections) and antipodality (i.e. di- ametrically opposed points in the unitary sphere) into a single primitive. The key idea of our transform is to study the different dihedral elements as a group of symmetries within the high-dimensional manifold. We obtain the respective set of mirror-symmetry axes by means of a frequency analysis of the dihedral elements, and we use them to collapse the redundant variability through a modified symmetry distance. The experimental validation of our algorithm shows the effectiveness of our approach, which obtains competitive quality with a dictionary of as little as 32 atoms (reducing other methods{\textquoteright} dictionaries by at least a factor of 32) and further pushing the state-of-the-art with a 1024 atoms dictionary.

}, url = {http://perezpellitero.github.io/}, author = {E. Perez-Pellitero and Salvador, J. and Ruiz-Hidalgo, J. and Rosenhahn, B.} } @conference {cPan, title = {Shallow and Deep Convolutional Networks for Saliency Prediction}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition, CVPR}, year = {2016}, month = {06/2016}, publisher = {Computer Vision Foundation / IEEE}, organization = {Computer Vision Foundation / IEEE}, address = {Las Vegas, NV, USA}, abstract = {

The prediction of salient areas in images has been traditionally addressed with hand-crafted features based on neuroscience principles. This paper, however, addresses the problem with a completely data-driven approach by training a convolutional neural network (convnet). The learning process is formulated as a minimization of a loss function that measures the Euclidean distance of the predicted saliency map with the provided ground truth. The recent publication of large datasets of saliency prediction has provided enough data to train end-to-end architectures that are both fast and accurate. Two designs are proposed: a shallow convnet trained from scratch, and a another deeper solution whose first three layers are adapted from another network trained for classification. To the authors knowledge, these are the first end-to-end CNNs trained and tested for the purpose of saliency prediction.

}, url = {http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Pan_Shallow_and_Deep_CVPR_2016_paper.pdf}, author = {Pan, Junting and McGuinness, Kevin and Elisa Sayrol and O{\textquoteright}Connor, N. and Xavier Gir{\'o}-i-Nieto} } @mastersthesis {xMontes, title = {Temporal Activity Detection in Untrimmed Videos with Recurrent Neural Networks}, year = {2016}, abstract = {

Advisors: Amaia Salvador and Xavier Gir{\'o}-i-Nieto.

Studies: Bachelor degree in Science and Telecommunication Technologies Engineering at\ Telecom BCN-ETSETB\ from the Technical University of Catalonia (UPC)

Grade: A (9.8/10.0)

This thesis explore different approaches using Convolutional and Recurrent Neural Networks to classify and temporally localize activities on videos, furthermore an implementation to achieve it has been proposed.

As the first step, features have been extracted from video frames using an state of the art 3D Convolutional Neural Network. This features are fed in a recurrent neural network that solves the activity classification and temporally location tasks in a simple and flexible way.

Different architectures and configurations have been tested in order to achieve the best performance and learning of the video dataset provided. In addition it has been studied different kind of post processing over the trained network{\textquoteright}s output to achieve a better results on the temporally localization of activities on the videos.

The results provided by the neural network developed in this thesis have been submitted to the ActivityNet Challenge 2016 of the CVPR, achieving competitive results using a simple and flexible architecture.

Temporal Activity Detection in Untrimmed Videos with Recurrent Neural Networks from Xavier Giro
}, keywords = {deep learning, neural networks, videos}, author = {Montes, Alberto}, editor = {Amaia Salvador and Xavier Gir{\'o}-i-Nieto} } @conference {cMontes, title = {Temporal Activity Detection in Untrimmed Videos with Recurrent Neural Networks}, booktitle = {1st NIPS Workshop on Large Scale Computer Vision Systems 2016}, year = {2016}, month = {12/2016}, abstract = {

This work proposes a simple pipeline to classify and temporally localize activities in untrimmed videos. Our system uses features from a 3D Convolutional Neural Network (C3D) as input to train a a recurrent neural network (RNN) that learns to classify video clips of 16 frames. After clip prediction, we post-process the output of the RNN to assign a single activity label to each video, and determine the temporal boundaries of the activity within the video. We show how our system can achieve competitive results in both tasks with a simple architecture. We evaluate our method in the ActivityNet Challenge 2016, achieving a 0.5874 mAP and a 0.2237 mAP in the classification and detection tasks, respectively. Our code and models are publicly available at:\ https://imatge-upc.github.io/activitynet-2016-cvprw/

}, author = {Montes, Alberto and Amaia Salvador and Pascual-deLaPuente, Santiago and Xavier Gir{\'o}-i-Nieto} } @conference {cIndia, title = {UPC System for the 2016 MediaEval Multimodal Person Discovery in Broadcast TV task}, booktitle = {MediaEval 2016 Workshop}, year = {2016}, month = {10/2016}, address = {Hilversum, The Netherlands}, abstract = {

The UPC system works by extracting monomodal signal segments (face tracks, speech segments) that overlap with the person names overlaid in the video signal. These segments are assigned directly with the name of the person and used as a reference to \ compare against the non-overlapping (unassigned) signal segments. This process is performed independently both on the speech and video signals. A simple fusion scheme is used to combine both monomodal annotations into a single one.

}, author = {India, M. and Mart{\'\i}, G. and Cotillas, C. and Bouritsas, G. and Elisa Sayrol and Morros, J.R. and Hernando, J.} } @conference {cPerez-Pellitero15, title = {Accelerating Super-Resolution for 4K Upscaling}, booktitle = {IEEE International Conference on Consumer Electronics}, year = {2015}, month = {01/2015}, address = {Las Vegas, NV, USA}, abstract = {

This paper presents a fast Super-Resolution (SR) algorithm based on a selective patch processing. Motivated by the observation that some regions of images are smooth and unfocused and can be properly upscaled with fast interpolation methods, we locally estimate the probability of performing a degradation-free upscaling. Our proposed framework explores the usage of supervised machine learning techniques and tackles the problem using binary boosted tree classifiers. The applied upscaler is chosen based on the obtained probabilities: (1) A fast upscaler (e.g. bicubic interpolation) for those regions which are smooth or (2) a linear regression SR algorithm for those which are ill-posed. The proposed strategy accelerates SR by only processing the regions which benefit from it, thus not compromising quality. Furthermore all the algorithms composing the pipeline are naturally parallelizable and further speed-ups could be obtained.

}, doi = {10.1109/ICCE.2015.7066429}, author = {E. Perez-Pellitero and Salvador, J. and Ruiz-Hidalgo, J. and Rosenhahn, B.} } @mastersthesis {xCabezas, title = {Co-filtering human interaction and object segmentation}, year = {2015}, abstract = {

Advisors: Axel Carlier and Vincent Charvillat (ENSEEIHT-Universit{\'e} de Toulouse) / Amaia Salvador and\ Xavier Gir{\'o}-i-Nieto\ (UPC)\ 

Degree: Audiovisual Engineering (4 years) at\ Telecom BCN-ETSETB\ (UPC)

Grade: A with honors (9.6/10)

For so many years the problem of object segmentation has been present in image processing field. Click{\textquoteright}n{\textquoteright}Cut, an already existing web tool for interactive object segmentation, helps us to obtain segmentations of the objects by clicking in green (foreground clicks) inside the object to segment, and in red(background clicks) outside the object to segment. However, the behaviour of all human in front of this web tool is not equal. For this reason, it can be possible that these human interactions do not help us to obtain a good object segmentation as would be the result of a bad human interaction. The main aim of this project is to implement some techniques that allow us to treat with these bad human interactions in order to obtain the best object segmentation possible.

Co-filtering human interaction and object segmentation from Xavi Gir{\'o}
}, url = {http://hdl.handle.net/2099.1/25821}, author = {Cabezas, Ferran}, editor = {Carlier, Axel and Amaia Salvador and Xavier Gir{\'o}-i-Nieto and Charvillat, Vincent} } @conference {cSalvadora, title = {Cultural Event Recognition with Visual ConvNets and Temporal Models}, booktitle = {CVPR ChaLearn Looking at People Workshop 2015}, year = {2015}, month = {06/2015}, abstract = {

This paper presents our contribution to the ChaLearn Challenge 2015 on Cultural Event Classification. The challenge in this task is to automatically classify images from 50 different cultural events. Our solution is based on the combination of visual features extracted from convolutional neural networks with temporal information using a hierarchical classifier scheme. We extract visual features from the last three fully connected layers of both CaffeNet (pretrained with ImageNet) and our fine tuned version for the ChaLearn challenge. We propose a late fusion strategy that trains a separate low-level SVM on each of the extracted neural codes. The class predictions of the low-level SVMs form the input to a higher level SVM, which gives the final event scores. We achieve our best result by adding a temporal refinement step into our classification scheme, which is applied directly to the output of each low-level SVM. Our approach penalizes high classification scores based on visual features when their time stamp does not match well an event-specific temporal distribution learned from the training and validation data. Our system achieved the second best result in the \ ChaLearn Challenge 2015 on Cultural Event Classification with a mean average precision of 0.767 on the test set.

[Preprint in arXiv][Workshop site][Slides on GDrive]

Cultural Event Recognition with Visual ConvNets and Temporal Models from Xavier Giro
}, url = {http://www.cv-foundation.org/openaccess/content_cvpr_workshops_2015/W09/papers/Salvador_Cultural_Event_Recognition_2015_CVPR_paper.pdf}, author = {Amaia Salvador and Zeppelzauer, Matthias and Manchon-Vizuete, Daniel and Calafell, Andrea and Xavier Gir{\'o}-i-Nieto} } @conference {cCampos-Camunez, title = {Diving Deep into Sentiment: Understanding Fine-tuned CNNs for Visual Sentiment Prediction}, booktitle = {1st International Workshop on Affect and Sentiment in Multimedia}, year = {2015}, month = {10/2015}, publisher = {ACM}, organization = {ACM}, address = {Brisbane, Australia}, abstract = {

Visual media are powerful means of expressing emotions and sentiments. The constant generation of new content in social networks highlights the need of automated visual sentiment analysis tools. While Convolutional Neural Networks (CNNs) have established a new state-of-the-art in several vision problems, their application to the task of sentiment analysis is mostly unexplored and there are few studies regarding how to design CNNs for this purpose. In this work, we study the suitability of fine-tuning a CNN for visual sentiment prediction as well as explore performance boosting techniques within this deep learning setting. Finally, we provide a deep-dive analysis into a benchmark, state-of-the-art network architecture to gain insight about how to design patterns for CNNs on the task of visual sentiment prediction.

Acceptance rate at the ASM workshop{\textquoteright}15: 56\% (9/16) [source]

Diving deep into sentiment: Understanding fine-tuned CNNs for visual sentiment prediction from Xavier Giro

Visual Sentiment Detection by Deep CNNs $\#$acmmm15 @DocXavi @mad_astronaut @brendanjou - great paper/analysis! pic.twitter.com/RcGchcPA9f

{\textemdash} Damian Borth (@damianborth) October 30, 2015
}, doi = {10.1145/2813524.2813530}, url = {http://arxiv.org/abs/1508.05056}, author = {V{\'\i}ctor Campos and Amaia Salvador and Xavier Gir{\'o}-i-Nieto and Jou, Brendan} } @conference {cTacchini, title = {Do you have a Pop face? Here is a Pop song. Using profile pictures to mitigate the cold-start problem in Music Recommender Systems}, booktitle = {9th ACM Conference on Recommender Systems}, year = {2015}, month = {09/2015}, author = {Tacchini, E. and Morros, J.R. and Ver{\'o}nica Vilaplana and Sa{\~n}oso, E.} } @conference {cMohedano, title = {Exploring EEG for Object Detection and Retrieval}, booktitle = {ACM International Conference on Multimedia Retrieval (ICMR) }, year = {2015}, address = {Shanghai, China}, abstract = {

This paper explores the potential for using Brain Computer Interfaces (BCI) as a relevance feedback mechanism in content-based image retrieval. We investigate if it is possible to capture useful EEG signals to detect if relevant objects are present in a dataset of realistic and complex images. \ We perform several experiments using a rapid serial visual presentation (RSVP) of images at different rates (5Hz and 10Hz) on 8 users with different degrees of familiarization with BCI and the dataset. We then use the feedback from the BCI and mouse-based interfaces to retrieve objects in a subset of TRECVid images. We show that it is indeed possible detect such objects in complex images and, also, that users with previous knowledge on the dataset or experience with the RSVP outperform others. When the users have limited time to annotate the images (100 seconds in our experiments) both interfaces are comparable in performance. Comparing our best users in a retrieval task, we found that EEG-based relevance feedback outperforms mouse-based feedback. The realistic and complex image dataset differentiates our work from previous studies on EEG for image retrieval.

[Extended version in arXiv:1504.02356]

[ACM ICMR 2015 website]

Overall acceptance rate: 33\% (source)

}, doi = {10.1145/2671188.2749368}, url = {http://arxiv.org/abs/1504.02356}, author = {Mohedano, Eva and Amaia Salvador and Porta, Sergi and Xavier Gir{\'o}-i-Nieto and Kevin McGuinness and Healy, Graham and O{\textquoteright}Connor, N.} } @mastersthesis {xCalafell-Oros, title = {Fine-tuning a Convolutional Network for Cultural Event Recognition}, year = {2015}, abstract = {

Advisors: Amaia Salvador (UPC), Matthias Zeppelzauer (FH St P{\"o}lten), Xavier Gir{\'o}-i-Nieto (UPC)

Studies: Bachelor Degree in Audiovisual Systems Engineering at Telecom BCN-ETSETB from the Technical University of Catalonia (UPC)

Grade: A with honors (10/10)

This thesis explores good practices for improving the performance of an existing convnet trained with a dataset of clean data when an additional dataset of noisy data is available. We develop techniques to clean the noisy data with the help of the clean one, a family of solutions that we will refer to as denoising, and then we explore the best sorting of the clean and noisy datasets during the fine-tuning of a convnet. Then we study strategies to select the subset of images of the clean data that will improve the classification performance, a practice we will efer to as fracking. Next, we determine how many layers are actually better to fine-tune in our convnet, given our amount of data. And finally, we compare the classic convnet architecture where a single network is fine-tuned to solve a multi-class problem with the case of fine-tuning a convnet for binary classification for each considered class.

Fine tuning a convolutional network for cultural event recognition from Xavier Giro

2015-TFG-AndreaCalafell-FineTuningConvolutionalNetworkForCulturalEventRecognition from Image Processing Group on Vimeo.

See https://imatge.upc.edu/web/publications/cultural-event-recognition-visual-convnets-and-temporal-models

}, url = {http://hdl.handle.net/2117/78391}, author = {Calafell, Andrea}, editor = {Amaia Salvador and Zeppelzauer, Matthias and Xavier Gir{\'o}-i-Nieto} } @article {aMohedano, title = {Improving Object Segmentation by using EEG signals and Rapid Serial Visual Presentation}, journal = {Multimedia Tools and Applications}, year = {2015}, month = {07/2015}, abstract = {

This paper explores the potential of brain-computer interfaces in segmenting objects from images. Our approach is centered around designing an effective method for displaying the image parts to the users such that they generate measurable brain reactions. When a block of pixels is displayed, we estimate the probability of that block containing the object of interest using a score based on EEG activity. After several such blocks are displayed in rapid visual serial presentation, the resulting probability map is binarized and combined with the GrabCut algorithm to segment the image into object and background regions. This study extends our previous work that showed how BCI and simple EEG analysis are useful in locating object boundaries in images

}, issn = {1573-7721}, doi = {10.1007/s11042-015-2805-0}, url = {http://dx.doi.org/10.1007/s11042-015-2805-0}, author = {Mohedano, Eva and Healy, Graham and Kevin McGuinness and Xavier Gir{\'o}-i-Nieto and O{\textquoteright}Connor, N. and Smeaton, Alan F.} } @conference {cMcGuinnessa, title = {Insight DCU at TRECVID 2015}, booktitle = {TRECVID 2015 Workshop}, year = {2015}, month = {11/2015}, publisher = {NIST}, organization = {NIST}, address = {Gaithersburg, MD, USA}, abstract = {

Insight-DCU participated in the instance search (INS), semantic indexing (SIN), and localization tasks (LOC) this year.

In the INS task we used deep convolutional network features trained on external data and the query data for this year to train our system. We submitted four runs, three based on convolutional network features, and one based on SIFT/BoW. F A insightdcu 1 was an automatic run using features from the last convolutional layer of a deep network with bag-of-words encoding and achieved 0.123 mAP. F A insightdcu 2 modi ed the previous run to use re-ranking based on an R-CNN model and achieved 0.111 mAP. I A insightdcu 3, our interactive run, achieved 0.269 mAP. Our SIFT-based run F A insightdcu 2 used weak geometric consistency to improve performance over the previous year to 0.187 mAP. Overall we found that using features from the convolutional layers improved performance over features from the fully connected layers used in previous years, and that weak geometric consistency improves performance for local feature ranking.

In the SIN task we again used convolutional network features, this time netuning a network pretrained on external data for the task. We submitted four runs, 2C D A insightdcu.15 1..4 varying the top-level learning algorithm and use of concept co-occurance. 2C D A insightdcu.15 1 used a linear SVM top-level learner, and achieved 0.63 mAP. Exploiting concept co-occurance improved the accuracy of our logistic regression run 2C D A insightdcu.15 3 from 0.058 mAP to 0.6 2C D A insightdcu.15 3.

Our LOC system used training data from IACC.1.B and features similar to our INS run, but using a VLAD encoding instead of a bag-of-words. Unfortunately there was problem with the run that we are still investigating.

Note: UPC and NII participated only in the INS task of this submission.

}, url = {http://www-nlpir.nist.gov/projects/tvpubs/tv.pubs.15.org.html}, author = {Kevin McGuinness and Mohedano, Eva and Amaia Salvador and Zhang, ZhenXing and Marsden, Mark and Wang, Peng and Jargalsaikhan, Iveel and Antony, Joseph and Xavier Gir{\'o}-i-Nieto and Satoh, Shin{\textquoteright}ichi and O{\textquoteright}Connor, N. and Smeaton, Alan F.} } @mastersthesis {xCampos-Camunez, title = {Layer-wise CNN Surgery for Visual Sentiment Prediction}, year = {2015}, abstract = {

Advisors: Amaia Salvador (UPC), Brendan Jou (Columbia University) and Xavier Gir{\'o}-i-Nieto (UPC)

Visual media are powerful means of expressing emotions and sentiments. The constant generation of new content in social networks highlights the need of automated visual sentiment analysis tools. While Convolutional Neural Networks (CNNs) have established a new state-of-the-art in several vision problems, their application to the task of sentiment analysis is mostly unexplored and there are few studies regarding how to design CNNs for this purpose. In this work, we study the suitability of fine-tuning a CNN for visual sentiment prediction as well as explore performance boosting techniques within this deep learning setting. Finally, we provide a deep-dive analysis into a benchmark, state-of-the-art network architecture to gain insight about how to design patterns for CNNs on the task of visual sentiment prediction.

Layer-wise CNN Surgery for Visual Sentiment Prediction from Xavier Giro

}, author = {V{\'\i}ctor Campos}, editor = {Amaia Salvador and Jou, Brendan and Xavier Gir{\'o}-i-Nieto} } @conference {cHuang15, title = {Mode dependent vector quantization with a rate-distortion optimized codebook for residue coding in video compression}, booktitle = {IEEE Int. Conf. on Acoustics Speech and Signal Processing, ICASSP 2015}, year = {2015}, month = {04/2015}, publisher = {IEEE}, organization = {IEEE}, address = {Brisbane, Australia}, abstract = {

The High Efficiency Video Coding standard (HEVC) supports a total of 35 intra prediction modes which aim at reducing spatial redundancy by exploiting pixel correlation within a local neighborhood. In this paper, we show that spatial correlation remains after intra prediction, leading to high energy prediction residues. We propose a novel scheme for encoding the prediction residues using a Mode Dependent Vector Quantization (MDVQ) which aims at reducing the redundancy in residual domain. The MDVQ codebook is optimized in a rate-distortion (RD) sense. Experimental results show that the codebook can be independent of the quantization parameter (QP) with no loss in terms of coding efficiency. A bitrate reduction of 1:1\% on average compared to HEVC can be achieved, while further tests indicate that codebook adaptivity could substantially improve the performance.

}, author = {Huang, B. and Henry, F. and Guillemot, C. and Salembier, P.} } @inbook {bDigne15, title = {Neighborhood Filters and the Recovery of 3D Information}, booktitle = {Handbook of Mathematical Methods in Imaging}, year = {2015}, pages = {1645-1673}, publisher = {Springer Verlag}, organization = {Springer Verlag}, edition = {2}, isbn = {978-1-4939-0789-2}, author = {J. Digne and Dimiccoli, M. and N. Sabater and Salembier, P.} } @article {aBellot Pujalte15, title = {NetBenchmark: a bioconductor package for reproducible benchmarks of gene regulatory network inference}, journal = {BMC Bioinformatics}, volume = {16}, year = {2015}, month = {09/2015}, abstract = {

Background:
In the last decade, a great number of methods for reconstructing gene regulatory networks from expression data have been proposed. However, very few tools and datasets allow to evaluate accurately and reproducibly those methods. Hence, we propose here a new tool, able to perform a systematic, yet fully reproducible, evaluation of transcriptional network inference methods.

Results:
Our open-source and freely available Bioconductor package aggregates a large set of tools to assess the robustness of network inference algorithms against different simulators, topologies, sample sizes and noise intensities.

Conclusions:
The benchmarking framework that uses various datasets highlights the specialization of some methods toward network types and data. As a result, it is possible to identify the techniques that have broad overall performances.

}, keywords = {Benchmark, Bioconductor package, Gene expression, Gene regulation network reconstruction, Gene regulatory networks, Synthetic genetic networks}, doi = {10.1186/s12859-015-0728-4}, url = {http://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0728-4}, author = {P. Bellot and Olsen, Catharina and Salembier, P. and Albert Oliveras and Meyer, P. E.} } @conference {cNguyen, title = {NII-HITACHI-UIT at TRECVID 2015 Instance Search}, booktitle = {TRECVID 2015 Workshop}, year = {2015}, month = {11/2015}, publisher = {NIST}, organization = {NIST}, address = {Gaithersburg, MD, USA}, abstract = {

In this paper, we propose two methods to improve last year instance search framework. Both of them are based on post processing scheme that try to rerank top K shots returned from BOW model. The rst system is to propose a query-adaptive weighting technique between DPM object detectors score and BOW{\textquoteright}s score. In order to nd a good weight, we use a neural network which learns characteristics of the query including number of features, number of shared words and area of the query topic. The second system combines two state-of-the-art object detectors: DPM and Fast RCNN to estimate object location and similarity score, respectively. The nal score is computed using these components together with BOW based similarity score returned from the baseline system. The experimental results show that our system improved pretty much even with a smaller number of top K input ranked list. Compared to other teams, we got the second place with the same run.

}, url = {http://www-nlpir.nist.gov/projects/tvpubs/tv.pubs.15.org.html}, author = {Nguyen, Vinh-Tiep and Duy-Dinh-Le and Amaia Salvador and Caizhi-Zhu and Nguyen, Dinh-Luan and Tran, Minh-Triet and Ngo Duc, Thanh and Anh Duong, Duc and Satoh, Shin{\textquoteright}ichi and Xavier Gir{\'o}-i-Nieto} } @article {aValero15, title = {Object recognition in hyperspectral images using Binary Partition Tree representation}, journal = {Pattern Recognition Letters}, volume = {56}, year = {2015}, month = {04/2015}, pages = {45-51}, abstract = {

In this work, an image representation based on Binary Partition Tree is proposed for object detection in hyperspectral images. This hierarchical region-based representation can be interpreted as a set of hierarchical regions stored in a tree structure, which succeeds in presenting: (i) the decomposition of the image in terms of coherent regions and (ii) the inclusion relations of the regions in the scene. Hence, the BPT representation defines a search space for constructing a robust object identification scheme. Spatial and spectral information are integrated in order to analyze hyperspectral images with a region-based perspective. For each region represented in the BPT, spatial and spectral descriptors are computed and the likelihood that they correspond to an instantiation of the object of interest is evaluated. Experimental results demonstrate the good performances of this BPT-based approach.

}, issn = {0167-8655}, author = {Valero, S. and Salembier, P. and Chanussot, J.} } @conference {cCabezas, title = {Quality Control in Crowdsourced Object Segmentation}, booktitle = {IEEE International Conference on Image Processing (ICIP), 2015}, year = {2015}, month = {09/2015}, abstract = {

This paper explores processing techniques to deal with noisy data in crowdsourced object segmentation tasks. We use the data collected with "Click{\textquoteright}n{\textquoteright}Cut", an online interactive segmentation tool, and we perform several experiments towards improving the segmentation results. First, we introduce different superpixel-based techniques to filter users{\textquoteright} traces, and assess their impact on the segmentation result. Second, we present different criteria to detect and discard the traces from potential bad users, resulting in a remarkable increase in performance. Finally, we show a novel superpixel-based segmentation algorithm which does not require any prior filtering and is based on weighting each user{\textquoteright}s contribution according to his/her level of expertise.

Selected among Top 10\% papers in ICIP 2015 based on the reviewer scores and recommendations.

[Preprint on arXiv]

[Related BSc thesis by Ferran Cabezas]

[IEEE ICIP 2015 conference website]

Co-filtering human interaction and object segmentation from Xavier Giro

}, url = {http://arxiv.org/abs/1505.00145}, author = {Cabezas, Ferran and Carlier, Axel and Amaia Salvador and Xavier Gir{\'o}-i-Nieto and Charvillat, Vincent} } @mastersthesis {xPorta, title = {Rapid Serial Visual Presentation for Relevance Feedback in Image Retrieval with EEG Signals}, year = {2015}, abstract = {

Studies: Bachelor degree in Science and Telecommunication Technologies Engineering at\ Telecom BCN-ETSETB\ from the Technical University of Catalonia (UPC)

Grade: A (9/10)

This thesis explores the potential of relevance feedback for image retrieval using EEG signals for human-computer interaction. This project aims at studying the optimal parameters of a rapid serial visual presentation (RSVP) of frames from a video database when the user is searching for an object instance. The simulations reported in this thesis assess the trade-off between using a small or a large amount of images in each RSVP round that captures the user feedback. While short RSVP rounds allow a quick learning of the user intention from the system, RSVP rounds must also be long enough to let users generate the P300 EEG signals which are triggered by relevant images. This work also addresses the problem of how to distribute potential relevant and non-relevant images in a RSVP round to maximize the probabilities of displaying each relevant frame separated at least 1 second from another relevant frame, as this configuration generates a cleaner P300 EEG signal. The presented simulations are based on a realistic set up for video retrieval with a subset of 1,000 frames from the TRECVID 2014 Instance Search task.

}, keywords = {eeg, feedback, image, relevance, retrieval}, author = {Porta, Sergi}, editor = {Amaia Salvador and Mohedano, Eva and Xavier Gir{\'o}-i-Nieto and O{\textquoteright}Connor, N.} } @mastersthesis {xBosch, title = {Region-oriented Convolutional Networks for Object Retrieval}, year = {2015}, abstract = {

Advisors: Amaia Salvador and\ Xavier Gir{\'o}-i-Nieto\ (UPC)\ 

Study program: Engineering on Audiovisual Systems (4 years) at Escola d{\textquoteright}Enginyeria de Terrassa\ (UPC)

Grade: A (9.6/10)

This thesis is framed in the computer vision field, addressing a challenge related to instance search. Instance search consists in searching for occurrences of a certain visual instance on a large collection of visual content, and generating a ranked list of results sorted according to their relevance to a user query. This thesis builds up on existing work presented at the TRECVID Instance Search Task in 2014, and explores the use of local deep learning features extracted from object proposals. The performance of different deep learning architectures (at both global and local scales) is evaluated, and a thorough comparison of them is performed. Secondly, this thesis presents the guidelines to follow in order to fine-tune a convolutional neural network for tasks such as image classification, object detection and semantic segmentation. It does so with the final purpose of fine tuning SDS, a CNN trained for both object detection and semantic segmentation, with the recently released Microsoft COCO dataset.

Region-oriented Convolutional Networks for Object Retrieval from Xavier Giro
}, author = {Fontdevila-Bosch, Eduard}, editor = {Amaia Salvador and Xavier Gir{\'o}-i-Nieto} } @conference {cSalembier15, title = {Study of Binary Partition Tree Pruning Techniques for Polarimetric SAR images}, booktitle = {International Symposium on Mathematical Morphology, ISMM 2015}, year = {2015}, month = {05/2015}, publisher = {Springer}, organization = {Springer}, address = {Reykjavik, Iceland}, isbn = {978-3-319-18719-8}, author = {Salembier, P.} } @conference {Bell1512:Study, title = {Study of Normalization and Aggregation Approaches for Consensus Network Estimation}, booktitle = {2015 IEEE Symposium Series on Computational Intelligence: IEEE Symposium on Artificial Life (2015 IEEE ALIFE)}, year = {2015}, address = {Cape Town, South Africa}, abstract = {

Inferring gene regulatory networks from expression data is a very difficult problem that has raised the interest of the scientific community. Different algorithms have been proposed to try to solve this issue, but it has been shown that the different methods have some particular biases and strengths, and none of them is the best across all types of data and datasets. As a result, the idea of aggregating various network inferences through a consensus mechanism naturally arises. In this paper, a common framework to standardize already proposed consensus methods is presented, and based on this framework different proposals are introduced and analyzed in two different scenarios: Homogeneous and Heterogeneous. The first scenario reflects situations where the networks to be aggregated are rather similar because the are obtained with inference algorithms working on the same data, whereas the second scenario deals with very diverse networks because various sources of data are used to generate the individual networks. A procedure for combining multiple network inference algorithms is analyzed in a systematic way. The results show that there is a very significant difference between these two scenarios, and that the best way to combine networks in the Heterogeneous scenario is not the most commonly used. We show in particular that aggregation in the Heterogeneous scenario can be very beneficial if the individual networks are combined with our new proposed method ScaleLSum.

}, author = {P. Bellot and Salembier, P. and Albert Oliveras and Meyer, P. E.} } @conference {cLidon, title = {UPC-UB-STP @ MediaEval 2015 Diversity Task: Iterative Reranking of Relevant Images}, booktitle = {MediaEval 2015 Workshop}, year = {2015}, month = {09/2015}, abstract = {

This paper presents the results of the UPC-UB-STP team in the 2015 MediaEval Retrieving Diverse Images Task.The goal of the challenge is to provide a ranked list of Flickr photos for a predefined set of queries. Our approach firstly generates a ranking of images based on a query-independent estimation of its relevance. Only top results are kept and iteratively re-ranked based on their intra-similarity to introduce diversity.

UPC-UB-STP @ MediaEval 2015 diversity task iterative reranking of relevant images from Xavier Giro
}, url = {http://ceur-ws.org/Vol-1436/}, author = {Lidon, Aniol and Bola{\~n}os, Marc and Seidl, Markus and Xavier Gir{\'o}-i-Nieto and Radeva, Petia and Zeppelzauer, Matthias} } @article {aTochon15, title = {On the use of binary partition trees for the tree crown segmentation of tropical rainforest hyperspectral images}, journal = {Remote Sensing of Environment}, volume = {159}, year = {2015}, month = {03/2015}, pages = {318-331}, abstract = {

The segmentation of remotely sensed images acquired over tropical forests is of great interest for numerous ecological applications, such as forest inventories or conservation and management of ecosystems, for which species classification techniques and estimation of the number of individuals are highly valuable inputs. In this paper, we propose a method for hyperspectral image segmentation, based on the binary partition tree (BPT) algorithm, and we apply it to two sites located in Hawaiian and Panamean tropical rainforests. Different strategies combining spatial and spectral dimensionality reduction are compared prior to the construction of the BPT. Various superpixel generation methods including watershed transformation and mean shift clustering are applied to decrease spatial dimensionality and provide an initial segmentation map. Principal component analysis is performed to reduce the spectral dimensionality and different combinations of principal components are compared. A non-parametric region model based on histograms, combined with the diffusion distance to merge regions, is used to build the BPT. An adapted pruning strategy based on the size discontinuity of the merging regions is proposed and compared with an already existing pruning strategy. Finally, a set of criteria to assess the quality of the tree segmentation is introduced. The proposed method correctly segmented up to 68\% of the tree crowns and produced reasonable patterns of the segmented landscapes.

}, issn = {0034-4257}, author = {G. Tochon and J.B. F{\'e}eret and Valero, S. and R.E. Martin and D.E. Knapp and Salembier, P. and Chanussot, J. and G. Asner} } @mastersthesis {xEscue, title = {Bundling interest points for object classification}, year = {2014}, abstract = {

Advisors: Xavier Giro-i-Nieto and Carles Ventura-Royo

Bundling interest points for object classification from Xavi Gir{\'o}

This Bachelor of Science thesis addresses the problem of image classification combining two popular visual representations: points and regions. Firstly, the study explores bundling interest points with regions. These regions are generated with an initial SLIC partition and using Binary Partition Tree (BPT), considering different scales of resolution in the segmentation. Secondly, it explores modelling visual classes as a group of points extracted from different images. Based on Naive-Bayes Nearest Neighbor (NBNN), we are using 1-Nearest Neighbor with SURF descriptor on the 17 Category Flower Dataset with 1360 images of flowers distributed into 17 classes, 80 images per class. We have verified that grouping interest points of the same class improves the F1-score a 9.2\%. However, bundling interest points into regions using segmentation worsens the F1-score between 1\% and 7\%, depending on the number of regions in the segmentation.

[Extended summary on Bitsearch blog]

Author{\textquoteright}s website: jordisanchez.info

Grade: A (9.3/10)

(This BSc thesis was written in Catalan language.)

---------------------------------

Aquest Treball Final de Grau aborda el problema de la classificaci{\'o} d{\textquoteright}imatges combinant dues representacions visuals populars: els punts i les regions. En primer lloc, l{\textquoteright}estudi explora l{\textquoteright}agrupaci{\'o} de punts d{\textquoteright}inter{\`e}s amb les regions. Aquestes regions es generen amb una partici{\'o} inicial SLIC i s{\textquoteright}utilitzen els Arbres de Partici{\'o} Bin{\`a}ria (Binary Partition Tree, BPT), considerant diferents escales de resoluci{\'o} en la segmentaci{\'o}. En segon lloc, s{\textquoteright}estudia modelar les classes com a grup de punts d{\textquoteright}inter{\`e}s extrets d{\textquoteright}imatges diferents. Basant-nos en el classificador Naive-Bayes Nearest Neighbor (NBNN), hem utilitzat el ve{\"\i} m{\'e}s proper amb un descriptor SURF sobre la base de dades 17 Category Flower Dataset, que cont{\'e} 1360 imatges de flors distribu{\"\i}des en 17 classes, amb 80 imatges per classe. Hem pogut verificar que el fet d{\textquoteright}ajuntar els punts d{\textquoteright}inter{\`e}s de les imatges d{\textquoteright}una mateixa classe millora la puntuaci{\'o} F1 en un 9,2\%. No obstant, l{\textquoteright}agrupaci{\'o} de punts d{\textquoteright}inter{\`e}s en regions utilitzant una segmentaci{\'o} de la imatge empitjora la puntuaci{\'o} F1 entre l{\textquoteright}1\% i el 7\%, depenent del nombre de regions de la segmentaci{\'o}.

Lloc web de l{\textquoteright}autor: jordisanchez.info

Qualificaci{\'o}: A (9.3/10)

Jordi Sanchez Escue

}, keywords = {Bundling interest points, Digital Images, image classification, Images, Nearest Neighbor, SURF}, url = {http://hdl.handle.net/2099.1/22672}, author = {S{\'a}nchez-Escu{\'e}, Jordi}, editor = {Ventura, C. and Xavier Gir{\'o}-i-Nieto} } @conference {cCarlier, title = {Click{\textquoteright}n{\textquoteright}Cut: Crowdsourced Interactive Segmentation with Object Candidates}, booktitle = {3rd International ACM Workshop on Crowdsourcing for Multimedia (CrowdMM)}, year = {2014}, month = {11/2014}, address = {Orlando, Florida (USA)}, abstract = {

This paper introduces Click{\textquoteright}n{\textquoteright}Cut, a novel web tool for interactive object segmentation addressed to crowdsourcing tasks. Click{\textquoteright}n{\textquoteright}Cut combines bounding boxes and clicks generated by workers to obtain accurate object segmentations. These segmentations are created by combining precomputed object candidates in a light computational fashion that allows an immediate response from the interface. Click{\textquoteright}n{\textquoteright}Cut has been tested with a crowdsourcing campaign to annotate a subset of the Berkeley Segmentation Dataset (BSDS). Results show competitive results with state of the art, especially in time to converge to a high quality segmentation. The data collection campaign included golden standard tests to detect cheaters.

[Related master thesis by Amaia Salvador]

[Related Phd thesis by Axel Carlier]

[CrowdMM website]

}, keywords = {Crowdsourcing, figure-ground segmentation, human computing, object candidates}, doi = {10.1145/2660114.2660125}, url = {http://dx.doi.org/10.1145/2660114.2660125}, author = {Carlier, Axel and Amaia Salvador and Xavier Gir{\'o}-i-Nieto and Marques, Oge and Charvillat, Vincent} } @article {aPaloua, title = {Depth order estimation for video frames using motion occlusions}, journal = {IET Computer Vision}, volume = {8}, year = {2014}, month = {04/2014}, pages = {152-160}, doi = {10.1049/iet-cvi.2012.0287}, author = {Palou, G. and Salembier, P.} } @conference {cBosch14, title = {An Epipolar-Constrained Prior for Efficient Search in Multi-View Scenarios}, booktitle = {EUSIPCO}, year = {2014}, month = {09/2014}, address = {Lisbon}, abstract = {

In this paper we propose a novel framework for fast exploitation of multi-view cues with applicability in different image processing problems. In order to bring our proposed framework into practice, an epipolar-constrained prior is presented, onto which a random search algorithm is proposed to find good matches among the different views of the same scene. This algorithm includes a generalization of the local coherency in 2D images for multi-view wide-baseline cases. Experimental results show that the geometrical constraint allows a faster initial convergence when finding good matches. We present some applications of the proposed framework on classical image processing problems.

}, keywords = {approximate nearest neighbor, deblurring, epipolar line, Super resolution}, author = {Bosch, I. and Salvador, J. and E. Perez-Pellitero and Ruiz-Hidalgo, J.} } @mastersthesis {xSalvador, title = {Exploiting User Interaction and Object Candidates for Instance Retrieval and Object Segmentation}, year = {2014}, abstract = {

Author: Amaia Salvador-Aguilera

Advisors:\ Xavier Gir{\'o}-i-Nieto\ (UPC) and Kevin McGuinness (Dublin CIty University)

Degree:\ Master in Computer Vision\ (1 year)

Video: Thesis defense

This thesis addresses two of the main challenges nowadays for computer vision: object segmentation and visual instance retrieval. The methodologies proposed to solve both problems are based on the use of object candidates and human computation in the computer vision loop. In the object segmentation side, this work explores how human computation can be useful to achieve better segmentation results, by combining users{\textquoteright} traces with a segmentation algorithm based on object candidates. On the other hand, the instance retrieval problem is also addressed using object candidates to compute local features, and involving the user in the retrieval loop by applying relevance feedback strategies.

}, keywords = {computer Vision, human computing, instance search, object candidates, segmentation}, author = {Amaia Salvador}, editor = {Xavier Gir{\'o}-i-Nieto and Kevin McGuinness} } @conference {cPerez-Pellitero14, title = {Fast Super-Resolution via Dense Local Training and Inverse Regressor Search}, booktitle = {Asian Conference in Computer Vision (ACCV)}, year = {2014}, month = {11/2014}, address = {Singapore}, abstract = {

Regression-based Super-Resolution (SR) addresses the up- scaling problem by learning a mapping function (i.e. regressor) from the low-resolution to the high-resolution manifold. Under the locally linear assumption, this complex non-linear mapping can be properly modeled by a set of linear regressors distributed across the manifold. In such methods, most of the testing time is spent searching for the right regressor within this trained set. In this paper we propose a novel inverse-search approach for regression-based SR. Instead of performing a search from the image to the dictionary of regressors, the search is done inversely from the regressors{\textquoteright} dictionary to the image patches. We approximate this framework by applying spherical hashing to both image and regressors, which reduces the inverse search into computing a trained function. Additionally, we propose an improved training scheme for SR linear regressors which improves perceived and objective quality. By merging both contributions we improve speed and quality compared to the state-of-the-art.

}, author = {E. Perez-Pellitero and Salvador, J. and Torres-Xirau, I. and Ruiz-Hidalgo, J. and Rosenhahn, B.} } @phdthesis {dBosio14, title = {Hierarchical information representation and efficient classification of gene expression microarray data}, volume = {PhD Thesis}, year = {2014}, month = {06/2014}, pages = {150}, school = {Universitat Politecnica de Catalunya}, address = {Barcelona}, abstract = {

In the field of computational biology, microarryas are used to measure the activity of thousands of genes at once and create a global picture of cellular function. Microarrays allow scientists to analyze expression of many genes in a single experiment quickly and efficiently. Even if microarrays are a consolidated research technology nowadays and the trends in high-throughput data analysis are shifting towards new technologies like Next Generation Sequencing (NGS), an optimum method for sample classification has not been found yet.

Microarray classification is a complicated task, not only due to the high dimensionality of the feature set, but also to an apparent lack of data structure. This characteristic limits the applicability of processing techniques, such as wavelet filtering or other filtering techniques that take advantage of known structural relation. On the other hand, it is well known that genes are not expressed independently from other each other: genes have a high interdependence related to the involved regulating biological process.

This thesis aims to improve the current state of the art in microarray classification and to contribute to understand how signal processing techniques can be developed and applied to analyze microarray data. The goal of building a classification framework needs an exploratory work in which algorithms are constantly tried and adapted to the analyzed data. The developed algorithms and classification frameworks in this thesis tackle the problem with two essential building blocks. The first one deals with the lack of a priori structure by inferring a data-driven structure with unsupervised hierarchical clustering tools. The second key element is a proper feature selection tool to produce a precise classifier as an output and to reduce the overfitting risk.

The main focus in this thesis is the binary data classification, field in which we obtained relevant improvements to the state of the art. The first key element is the data-driven structure, obtained by modifying hierarchical clustering algorithms derived from the Treelets algorithm from the literature. Several alternatives to the original reference algorithm have been tested, changing either the similarity metric to merge the feature or the way two feature are merged. Moreover, the possibility to include external sources of information from publicly available biological knowledge and ontologies to improve the structure generation has been studied too. About the feature selection, two alternative approaches have been studied: the first one is a modification of the IFFS algorithm as a wrapper feature selection, while the second approach involved an ensemble learning focus. To obtain good results, the IFFS algorithm has been adapted to the data characteristics by introducing new elements to the selection process like a reliability measure and a scoring system to better select the best feature at each iteration. The second feature selection approach is based on Ensemble learning, taking advantage of the microarryas feature abundance to implement a different selection scheme. New algorithms have been studied in this field, improving state of the art algorithms to the microarray data characteristic of small sample and high feature numbers.

In addition to the binary classification problem, the multiclass case has been addressed too. A new algorithm combining multiple binary classifiers has been evaluated, exploiting the redundancy offered by multiple classifiers to obtain better predictions.

All the studied algorithm throughout this thesis have been evaluated using high quality publicly available data, following established testing protocols from the literature to offer a proper benchmarking with the state of the art.

Whenever possible, multiple Monte Carlo simulations have been performed to increase the robustness of the obtained results.\ 

}, url = {http://hdl.handle.net/10803/145902}, author = {Bosio, M.}, editor = {Salembier, P. and Albert Oliveras} } @conference {cMcGuinness, title = {Insight Centre for Data Analytics (DCU) at TRECVid 2014: Instance Search and Semantic Indexing Tasks}, booktitle = {2014 TRECVID Workshop}, year = {2014}, month = {11/2014}, publisher = {National Institute of Standards and Technology (NIST)}, organization = {National Institute of Standards and Technology (NIST)}, address = {Orlando, Florida (USA)}, abstract = {

Insight-DCU participated in the instance search (INS) and semantic indexing (SIN) tasks in 2014. Two very different approaches were submitted for instance search, one based on features extracted using pre-trained deep convolutional neural networks (CNNs), and another based on local SIFT features, large vocabulary visual bag-of-words aggregation, inverted index-based lookup, and geometric verification on the top-N retrieved results. Two interactive runs and two automatic runs were submitted, the best interactive runs achieved a mAP of 0.135 and the best automatic 0.12. Our semantic indexing runs were based also on using convolutional neural network features, and on Support Vector Machine classifiers with linear and RBF kernels. One run was submitted to the main task, two to the no annotation task, and one to the progress task. Data for the no-annotation task was gathered from Google Images and ImageNet. The main task run has achieved a mAP of 0.086, the best no-annotation runs had a close performance to the main run by achieving a mAP of 0.080, while the progress run had 0.043.

[2014 TREC Video Retrieval Evaluation Notebook Papers and Slides]

Poster

}, url = {http://hdl.handle.net/2117/24915}, author = {Kevin McGuinness and Mohedano, Eva and Zhang, ZhenXing and Hu, Feiyan and Albatal, Rami and Gurrin, Cathal and O{\textquoteright}Connor, N. and Smeaton, Alan F. and Amaia Salvador and Xavier Gir{\'o}-i-Nieto and Ventura, C.} } @conference {cSalembier14, title = {Low-level processing of PolSAR images with binary partition trees}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2014}, year = {2014}, month = {07/2014}, publisher = {IEEE}, organization = {IEEE}, address = {Quebec, Canada}, abstract = {

This paper discusses the interest of Binary Partition Trees (BPTs) and the usefulness of graph cuts for low-level processing of PolSAR images. BPTs group pixels to form homogeneous regions, which are hierarchically structured by inclusion in a tree. They provide multiple resolutions of description and easy access to subsets of regions. Once constructed, BPTs can be used for many applications including filtering, segmentation, classification and object detection. Many processing strategies consist in populating the tree with a specific feature and in applying a graph-cut called pruning. Different graph-cuts are discussed and analyzed in the context of PolSAR images for speckle filtering and segmentation.

}, author = {Salembier, P. and S. Foucher and L{\'o}pez-Mart{\'\i}nez, C.} } @conference {cMorros14, title = {Materials transversals per a l{\textquoteright}aprenentatge actiu de les mat{\`e}ries de processat d{\textquoteright}imatge i v{\'\i}deo}, booktitle = {Congr{\'e}s Internacional de Doc{\`e}ncia Universit{\`a}ria i Innovaci{\'o} (CIDUI)}, year = {2014}, month = {07/2014}, address = {Tarragona, Spain}, abstract = {

This work aims to promote the cooperation and coordination between different image/video processing courses taught at the UPC in order to enhance the learning results. The main contributions are a) the creation of a common set of materials: graphical demonstrators, collections of problems, question banks, etc. and b) the design of strategies strategies to use this material in the development of generic and specific skills, with special emphasis on promoting independent learning

}, keywords = {image/video processing, Matlab demonstrators, question Banks, specific skills, teaching material}, author = {Morros, J.R. and Ver{\'o}nica Vilaplana and Ruiz-Hidalgo, J. and Casas, J. and Gasull, A. and Marqu{\'e}s, F. and M. Pard{\`a}s and Salembier, P.} } @book {bSchreer14, title = {Media Production, Delivery and Interaction for Platform Independent Systems}, volume = {ISBN 978-1-118-60533-2}, year = {2014}, publisher = {Wiley, ISBN 978-1-118-60533-2}, organization = {Wiley, ISBN 978-1-118-60533-2}, issn = {978-1-118-60533-2}, url = {http://eu.wiley.com/WileyCDA/WileyTitle/productCd-1118605330,subjectCd-EEJ0.html}, author = {Schreer, O. and Macq, J. and Niamut, O. and Ruiz-Hidalgo, J. and Shirley, B. and Thallinger, G. and Thomas, G.} } @phdthesis {dPalou14, title = {Monocular Depth Estimation in Images and Sequences using Occlusion Cues}, volume = {PhD}, year = {2014}, month = {02/2014}, pages = {250}, abstract = {

When humans observe a scene, they are able to perfectly distinguish the different parts composing it. Moreover, humans can easily reconstruct the spatial position of these parts and conceive a consistent structure. The mechanisms involving visual perception have been studied since the beginning of neuroscience but, still today, not all the processes composing it are known. In usual situations, humans can make use of three different methods to estimate the scene structure. The first one is the so called divergence and it makes use of both eyes. \ When objects lie in front of the observed at a distance up to hundred meters, subtle differences in the image formation in each eye can be used to determine depth. When objects are not in the field of view of both eyes, other mechanisms should be used. In these cases, both visual cues and prior learned information can be used to determine depth. Even if these mechanisms are less accurate than divergence, humans can almost always infer the correct depth structure when using them. As an example of visual cues, occlusion, perspective or object size provide a lot of information about the structure of the scene. A priori information depends on each observer, but it is normally used subconsciously by humans to detect commonly known regions such as the sky, the ground or different types of objects.

In the last years, since technology has been able to handle the processing burden of vision systems, there has been lots of efforts devoted to design automated scene interpreting systems. In this thesis we address the problem of depth estimation using only one point of view and using only occlusion depth cues. The thesis objective is to detect occlusions present in the scene \ and combine them with a segmentation system so as to generate a relative depth order depth map for a scene. We explore both static and dynamic situations such as single images, frame inside sequences or full video sequences. In the case where a full image sequence is available, a system exploiting motion information to recover depth structure is also designed. Results are promising and competitive with respect to the state of the art literature, but there is still much room for improvement when compared to human depth perception performance.

}, url = {http://hdl.handle.net/10803/144653}, author = {Palou, G.}, editor = {Salembier, P.} } @conference {cAlonso-Gonzalez14, title = {Multidimensional SAR Data Analysis Based on Binary Partition Trees and the Covariance Matrix Geometry}, booktitle = {International Radar Conference 2014}, year = {2014}, month = {10/2014}, publisher = {SEE}, organization = {SEE}, address = {Lille, France}, abstract = {

In this paper, we propose the use of the Binary Partition Tree (BPT) as a region-based and multi-scale image representation to process multidimensional SAR data, with special emphasis on polarimetric SAR data. We also show that this approach could be extended to other types of remote sensing imaging technologies, such as hyperspatial imagery. The Binary Partition Tree contains a lot of information about the image structure at different detail levels. At the same time, this structure represents a convenient vehicle to exploit both the statistical properties, as well as the geometric properties of the multidimensional SAR data given by the covariance matrix. The BPT construction process and its exploitation for PolSAR and temporal data information estimation is analyzed in this work. In particular, this work focuses on the speckle noise filtering problem and the temporal characterization of the image dynamics. Results with real data are presented to illustrate the capabilities of the BPT processing approach, specially to maintain the spatial resolution and the small details of the image.

}, author = {Alonso-Gonz{\'a}lez, A. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P.} } @conference {cMohedano, title = {Object segmentation in images using EEG signals}, booktitle = {ACM Multimedia}, year = {2014}, month = {11/2014}, address = {Orlando, Florida (USA)}, abstract = {

This paper explores the potential of brain-computer interfaces in segmenting objects from images. Our approach is centered around designing an effective method for displaying the image parts to the users such that they generate measurable brain reactions. When an image region, specifically a block of pixels, is displayed we estimate the probability of the block containing the object of interest using a score based on EEG activity. After several such blocks are displayed, the resulting probability map is binarized and combined with the GrabCut algorithm to segment the image into object and background regions. This study shows that BCI and simple EEG analysis are useful in locating object boundaries in images.

}, keywords = {Brain-computer interfaces, Electroencephalography, GrabCut algorithm, Interactive segmentation, Object segmentation, rapid serial visual presentation}, doi = {10.1145/2647868.2654896}, url = {http://arxiv.org/abs/1408.4363}, author = {Mohedano, Eva and Healy, Graham and Kevin McGuinness and Xavier Gir{\'o}-i-Nieto and O{\textquoteright}Connor, N. and Smeaton, Alan F.} } @article {aAlonso-Gonzalez, title = {PolSAR Time Series Processing with Binary Partition Trees}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, volume = {52}, year = {2014}, month = {06/2014}, pages = {3553 {\textendash} 3567}, abstract = {

This paper deals with the processing of polarimetric synthetic aperture radar (SAR) time series. Different approaches to deal with the temporal dimension of the data are considered, which are derived from different target characterizations in this dimension. These approaches are the basis for defining two different binary partition tree (BPT) structures that are employed for SAR polarimetry (PolSAR) data processing. Once constructed, the BPT is processed by a tree pruning, producing a set of spatiotemporal homogeneous regions, and estimating the polarimetric response within them. It is demonstrated that the proposed technique preserves the PolSAR information in the spatial and the temporal domains without introducing bias nor distortion. Additionally, the evolution of the data in the temporal dimension is also analyzed, and techniques to obtain BPT-based scene change maps are defined. Finally, the proposed techniques are employed to process two real RADARSAT-2 data sets.

}, issn = {0196-2892}, doi = {10.1109/TGRS.2013.2273664}, author = {Alonso-Gonz{\'a}lez, A. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P.} } @conference {cPalou14, title = {Precision-Recall-Classification Evaluation Framework: Application to Depth Estimation on Single Images}, booktitle = {European Conference on Computer Vision (ECCV)}, year = {2014}, month = {09/2014}, address = {Zurich}, abstract = {

Many computer vision applications involve algorithms that can be decomposed in two main steps. In a first step, \ events or objects are detected and, in a subsequent stage, detections are assigned to various classes. Examples of such {\textquoteleft}{\textquoteleft}detection plus classification{\textquoteright}{\textquoteright} problems can be found in human pose classification, object recognition or action classification among others. In this paper, we focus on a special case: depth ordering on single images. In this \ problem, the detection step consists of the image segmentation, and the classification stage assigns a depth gradient to each contour or a depth order to each region.

In this paper, we discuss the limitations of the classical Precision-Recall evaluation framework for these kind of problems and define an extended framework called {\textquoteleft}{\textquoteleft}Precision-Recall-Classfication{\textquoteright}{\textquoteright} (PRC). Then, we apply this framework to depth ordering problems and design two specific PRC

measures to evaluate both the local and the global depth consistencies. We use these measures to evaluate precisely state of the art depth ordering systems for monocular images. Based on this evaluation, we also propose an extension to the method of [Cal13] applying an optimal graph cut on a hierarchical segmentation structure such as ultrametric contour maps. The resulting system is proven to provide better results than state of the art algorithms.

}, author = {Palou, G. and Salembier, P.} } @article {Suau2014, title = {Real-time Fingertip Localization Conditioned on Hand Gesture Classification}, journal = {Image and Vision Computing}, volume = {32}, year = {2014}, month = {05/2014}, pages = {522 - 532}, abstract = {

A method to obtain accurate hand gesture classification and fingertip localization from depth images is proposed. The Oriented Radial Distribution feature is utilized, exploiting its ability to globally describe hand poses, but also to locally detect fingertip positions. Hence, hand gesture and fingertip locations are characterized with a single feature calculation. We propose to divide the difficult problem of locating fingertips into two more tractable problems, by taking advantage of hand gesture as an auxiliary variable. Along with the method we present the ColorTip dataset, a dataset for hand gesture recognition and fingertip classification using depth data. ColorTip contains sequences where actors wear a glove with with colored fingertips, allowing automatic annotation. The proposed method is evaluated against recent works in several datasets, achieving promising results in both gesture classification and fingertip localization.

}, keywords = {dataset, fingertip classification, hand gesture recognition, interactivity, range camera}, issn = {0262-8856}, doi = {10.1016/j.imavis.2014.04.015}, url = {http://www.sciencedirect.com/science/article/pii/S0262885614000845}, author = {Suau, X. and Alcoverro, M. and L{\'o}pez-M{\'e}ndez, A. and Ruiz-Hidalgo, J. and Casas, J.} } @article {aSalembier14, title = {Remote sensing image processing with graph cut of Binary Partition Trees}, journal = {Advances in computing science, control and communications}, volume = {69}, year = {2014}, month = {04/2014}, pages = {185-196}, issn = {1870-4069}, author = {Salembier, P. and S. Foucher} } @conference {cPerez-Pellitero13, title = {Bayesian region selection for adaptive dictionary-based Super-Resolution}, booktitle = {British Machine Vision Conference}, year = {2013}, month = {09/2013}, abstract = {

The performance of dictionary-based super-resolution (SR) strongly depends on the contents of the training dataset. Nevertheless, many dictionary-based SR methods randomly select patches from of a larger set of training images to build their dictionaries,\ thus relying on patches being diverse enough. This paper describes an external-dictionary SR algorithm based on adaptively selecting an optimal subset of patches out of the training images. Each training image is divided into sub-image entities, named regions, of such size that texture consistency is preserved. For each input patch to super-resolve, the best-fitting region (with enough high-frequency energy) is found through a Bayesian selection. In order to handle the high number of regions in the train- ing dataset, a local Naive Bayes Nearest Neighbor (NBNN) approach is used. Trained with this adapted subset of patches, sparse coding SR is applied to recover the high-resolution image. Experimental results demonstrate that using our adaptive algorithm produces an improvement in SR performance with respect to non-adaptive training.\ 

}, author = {E. Perez-Pellitero and Salvador, J. and Ruiz-Hidalgo, J. and Rosenhahn, B.} } @article {aAlonso-Gonzalez13a, title = {Bilateral Distance Based Filtering for Polarimetric SAR Data}, journal = {Remote Sensing}, volume = {5}, year = {2013}, month = {10/2013}, pages = {5620-5641}, abstract = {

This paper introduces a non-linear Polarimetric SAR data filtering approach able to preserve the edges and small details of the data. It is based on exploiting the data locality in both, the spatial and the polarimetric domains, in order to avoid mixing heterogeneous samples of the data. A weighted average is performed over a given window favoring pixel values that are close on both domains. The filtering technique is based on a modified bilateral filtering, which is defined in terms of spatial and polarimetric distances. These distances encapsulate all the knowledge in both domains for an adaptation to the data structure. Finally, the proposed technique is employed to process a real RADARSAT-2 dataset.

}, issn = {2072-4292}, doi = {10.3390/rs5115620}, author = {Alonso-Gonz{\'a}lez, A. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P. and X. Deng} } @conference {cSalvador13 , title = {Crowdsourced Object Segmentation with a Game}, booktitle = {ACM Workshop on Crowdsourcing for Multimedia (CrowdMM)}, year = {2013}, month = {10/2013}, address = {Barcelona}, abstract = {

We introduce a new algorithm for image segmentation based on crowdsourcing through a game : Ask{\textquoteright}nSeek. The game provides information on the objects of an image, under the form of clicks that are either on the object, or on the background. These logs are then used in order to determine the best segmentation for an object among a set of candidates generated by the state-of-the-art CPMC algorithm. We also introduce a simulator that allows the generation of game logs and therefore gives insight about the number of games needed on an image to perform acceptable segmentation.

Amaia Salvador, "Crowdsourced Object Segmentation with a Game" from Xavi Gir{\'o}
}, isbn = {978-1-4503-2396-3}, doi = {http://dx.doi.org/10.1145/2506364.2506367}, url = {http://dx.doi.org/10.1145/2506364.2506367}, author = {Amaia Salvador and Carlier, Axel and Xavier Gir{\'o}-i-Nieto and Marques, Oge and Charvillat, Vincent} } @mastersthesis {xSalvador13, title = {Crowdsourced Object Segmentation with a Game}, year = {2013}, abstract = {

Co-advised with Axel Carlier (INP Toulouse), Vincent Charvillat\ (INP Toulouse) and Oge Marques (Florida Atlantic University).

Amaia Salvador, "Crowdsourced Object Segmentation with a Game" from Image Processing Group on Vimeo.

}, author = {Amaia Salvador}, editor = {Xavier Gir{\'o}-i-Nieto and Carlier, Axel and Charvillat, Vincent and Marques, Oge} } @article {aSuau13, title = {Detecting End-Effectors on 2.5D data using Geometric Deformable Models: Application to Human Pose Estimation}, journal = {Computer Vision and Image Understanding (CVIU)}, volume = {117}, year = {2013}, chapter = {281{\textendash}288}, abstract = {

End-effectors are usually related to the location of limbs, and their reliable detection enables robust body tracking as well as accurate pose estimation. Recent innovation in depth cameras has re-stated the pose estimation problem. We focus on the information provided by these sensors, for which we borrow the name 2.5D data from the Graphics community. In this paper we propose a human pose estimation algorithm based on topological propagation. Geometric Deformable Models are used to carry out such propagation, implemented according to the Narrow Band Level Set approach. A variant of the latter method is proposed, including a density restriction which helps preserving the topological properties of the object under analysis. Principal end-effectors are extracted from a directed graph weighted with geodesic distances, also providing a skeletal-like structure describing human pose. An evaluation against reference methods is performed with promising results. The proposed solution allows a frame-wise end-effector detection, with no temporal tracking involved, which may be generalized to the tracking of other objects beyond human body.

}, doi = {10.1016/j.cviu.2012.11.006}, url = {http://www.sciencedirect.com/science/article/pii/S1077314212001907}, author = {Suau, X. and Ruiz-Hidalgo, J. and Casas, J.} } @conference {cBosio13a, title = {Ensemble learning and hierarchical data representation for microarray classification}, booktitle = {13th IEEE International Conference on BioInformatics and BioEngineering BIBE}, year = {2013}, month = {11/2013}, publisher = {13th IEEE International Conference on BioInformatics and BioEngineering,}, organization = {13th IEEE International Conference on BioInformatics and BioEngineering,}, address = {Chania, Crete}, abstract = {

Microarray data classification is an open and active research field.

The development of more accurate algorithms is of great interest also because many of the techniques can be straightforwardly applied in analyzing different kinds of omics data.

In this work, an ensemble feature selection algorithm is applied within a binary classification framework from [1] that already got good predictive results. Ensemble feature selection is a rich field of research.

Ensemble techniques take some individual experts (i.e. classifiers) to combine them to improve the individual expert results with a voting scheme.

In this case, a thinning algorithm is proposed which starts by using all the available experts and removes them one by one focusing on improving the ensemble vote.

Two versions of an ensemble thinning algorithm have been tested and three key elements have been introduced to work with microarray data: the ensemble cohort definition, the nonexpert notion, which defines a set of excluded expert from the thinning process, and a rule to break ties in the thinning process. Experiments have been done on seven public datasets from the Microarray Quality Control study, MAQC [2].

The studied ensemble technique improves the state of the art results by producing classifiers with significantly better results and the proposed key elements have shown to be useful for the prediction performance.

}, keywords = {Microarray classification; metagenes; hierarchical representation; Treelets; feature selection; LDA; ensemble.}, author = {Bosio, M. and Salembier, P. and Albert Oliveras and P. Bellot} } @mastersthesis {xGarcia-delMolino13, title = {Extension of Instance Search Technique by Geometric Coding and Quantization Error Compensation}, year = {2013}, abstract = {

This MSc thesis analyzes two ways of improving the video retrieval techniques for instance search problem. In one hand, "Pairing Interest Points for a better Signature using Sparse Detector{\textquoteright}s Spatial Information", allows the Bag-of-Words model to keep some spatial information. In the other, "Study of the Hamming Embedding Signature Symmetry in Video Retrieval" provides binary signatures that refine the matching based on visual words, and aims to find the best way of matching taking into account the existent asymmetries between image query and videos.

}, url = {http://hdl.handle.net/2099.1/19159}, author = {Garcia-delMolino, Ana}, editor = {Satoh, Shin{\textquoteright}ichi and Ventura, C. and Xavier Gir{\'o}-i-Nieto} } @article {aAlcoverro13, title = {Gesture Control Interface for immersive panoramic displays}, journal = {Multimedia Tools and Applications}, year = {2013}, month = {07/2013}, pages = {1-27}, abstract = {

In this paper, we propose a gesture-based interface designed to interact with panoramic scenes. The system combines novel static gestures with a fast hand tracking method. Our proposal is to use static gestures as shortcuts to activate functionalities of the system (i.e. volume up/down, mute, pause, etc.), and hand tracking to freely explore the panoramic video. The overall system is multi-user, and incorporates a user identi cation module based on face recognition, which is able both to recognize returning users and to add new users online. The system exploits depth data, making it robust to challenging illumination conditions. We show through experimental results the performance of every component of the system compared to the state of the art. We also show the results of a usability study\ performed with several untrained users.

}, issn = {1380-7501}, doi = {10.1007/s11042-013-1605-7}, author = {Alcoverro, M. and Suau, X. and Morros, J.R. and L{\'o}pez-M{\'e}ndez, A. and A. Gil-Moreno and Ruiz-Hidalgo, J. and Casas, J.} } @conference {cBosio13, title = {Hierarchical Clustering Combining Numerical and Biological Similarities for Gene Expression Data Classification}, booktitle = {35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC{\textquoteright}13) }, year = {2013}, month = {07/2013}, publisher = {IEEE EMBS}, organization = {IEEE EMBS}, address = {Osaka, Japan}, keywords = {Biological interpretation, Hierarchical representation, microarray classification}, author = {Bosio, M. and Salembier, P. and P. Bellot and Albert Oliveras} } @conference {cPalou13, title = {Hierarchical Video Representation with Trajectory Binary Partition Tree}, booktitle = {Computer Vision and Pattern Recognition (CVPR)}, year = {2013}, month = {06/2013}, address = {Portland, Oregon}, abstract = {

As early stage of video processing, we introduce an iterative trajectory merging algorithm that produces a region-based and hierarchical representation of the video sequence, called the Trajectory Binary Partition Tree (BPT). From this representation, many analysis and graph cut techniques can be used to extract partitions or objects that are useful in the context of specific applications.\ 

In order to define trajectories and to create a precise merging algorithm, color and motion cues have to be used. Both types of informations are very useful to characterize objects but present strong differences of behavior in the spatial and the temporal dimensions. On the one hand, scenes and objects are rich in their spatial color distributions, but these distributions are rather stable over time. Object motion, on the other hand, presents simple structures and low spatial variability but may change from frame to frame. The proposed algorithm takes into account this key difference and relies on different models and associated metrics to deal with color and motion information. We show that the proposed algorithm outperforms existing hierarchical video segmentation algorithms and provides more stable and precise regions.

}, author = {Palou, G. and Salembier, P.} } @phdthesis {dSuau13, title = {Human body analysis using depth data}, year = {2013}, school = {Universitat Polit{\`e}cnica de Catalunya (UPC)}, type = {phd}, abstract = {

Human body analysis is one of the broadest areas within the computer vision field. Researchers have put a strong effort in the human body analysis area, specially over the last decade, due to the technological improvements in both video cameras and processing power. Human body analysis covers topics such as person detection and segmentation, human motion tracking or action and behavior recognition. Even if human beings perform all these tasks naturally, they build-up a challenging problem from a computer vision point of view. Adverse situations such as viewing perspective, clutter and occlusions, lighting conditions or variability of behavior amongst persons may turn human body analysis into an arduous task.

In the computer vision field, the evolution of research works is usually tightly related to the technological progress of camera sensors and computer processing power. Traditional human body analysis methods are based on color cameras. Thus, the information is extracted from the raw color data, strongly limiting the proposals. An interesting quality leap was achieved by introducing the \emph{multiview} concept. That is to say, having multiple color cameras recording a single scene at the same time. With multiview approaches, 3D information is available by means of stereo matching algorithms. The fact of having 3D information is a key aspect in human motion analysis, since the human body moves in a three-dimensional space. Thus, problems such as occlusion and clutter may be overcome with 3D information.

The appearance of commercial depth cameras has supposed a second leap in the human body analysis field. While traditional multiview approaches required a cumbersome and expensive setup, as well as a fine camera calibration; novel depth cameras directly provide 3D information with a single camera sensor. Furthermore, depth cameras may be rapidly installed in a wide range of situations, enlarging the range of applications with respect to multiview approaches. Moreover, since depth cameras are based on infra-red light, they do not suffer from illumination variations.

In this thesis, we focus on the study of depth data applied to the human body analysis problem. We propose novel ways of describing depth data through specific descriptors, so that they emphasize helpful characteristics of the scene for further body analysis. These descriptors exploit the special 3D structure of depth data to outperform generalist 3D descriptors or color based ones. We also study the problem of person detection, proposing a highly robust and fast method to detect heads. Such method is extended to a hand tracker, which is used throughout the thesis as a helpful tool to enable further research. In the remainder of this dissertation, we focus on the hand analysis problem as a subarea of human body analysis. Given the recent appearance of depth cameras, there is a lack of public datasets. We contribute with a dataset for hand gesture recognition and fingertip localization using depth data. This dataset acts as a starting point of two proposals for hand gesture recognition and fingertip localization based on classification techniques. In these methods, we also exploit the above mentioned descriptor proposals to finely adapt to the nature of depth data.

}, url = {http://hdl.handle.net/10803/134801}, author = {Suau, X.}, editor = {Casas, J. and Ruiz-Hidalgo, J.} } @article {aValero13, title = {Hyperspectral image representation and processing with Binary Partition Trees}, journal = {IEEE Transactions on Image Processing}, volume = {22}, year = {2013}, month = {April 2013}, pages = {1430 - 1443}, abstract = {

The optimal exploitation of the information provided by hyperspectral images requires the development of advanced image-processing tools. This paper proposes the construction and the processing of a new region-based hierarchical hyperspectral image representation relying on the binary partition tree (BPT). This hierarchical region-based representation can be interpreted as a set of hierarchical regions stored in a tree structure. Hence, the BPT succeeds in presenting: 1) the decomposition of the image in terms of coherent regions, and 2) the inclusion relations of the regions in the scene. Based on region-merging techniques, the BPT construction is investigated by studying the hyperspectral region models and the associated similarity metrics. Once the BPT is constructed, the fixed tree structure allows implementing efficient and advanced application-dependent techniques on it. The applicationdependent processing of BPT is generally implemented through a specific pruning of the tree. In this paper, a pruning strategy is proposed and discussed in a classification context. Experimental results on various hyperspectral data sets demonstrate the interest and the good performances of the BPT representation.

}, doi = {10.1109/TIP.2012.2231687}, author = {Valero, S. and Salembier, P. and Chanussot, J.} } @article {aPalou13, title = {Monocular Depth Ordering Using T-junctions and Convexity Occlusion Cues}, journal = {IEEE Transactions on Image Processing}, volume = {22}, year = {2013}, month = {2013}, pages = { 1926 - 1939 }, abstract = {

This paper proposes a system that relates objects in an image using occlusion cues and arranges them according to depth. The system does not rely on a priori knowledge of the scene structure and focuses on detecting special points, such as T-junctions and highly convex contours, to infer the depth relationships between objects in the scene. The system makes extensive use of the binary partition tree as hierarchical region-based image representation jointly with a new approach for candidate T-junction estimation. Since some regions may not involve T-junctions, occlusion is also detected by examining convex shapes on region boundaries. Combining T-junctions and convexity leads to a system which only relies on low level depth cues and does not rely on semantic information. However, it shows a similar or better performance with the state-of-the-art while not assuming any type of scene.

}, doi = {10.1109/TIP.2013.2240002}, author = {Palou, G. and Salembier, P.} } @article {aSalvador13, title = {Multi-View Video Representation Based on Fast Monte Carlo Surface Reconstruction}, journal = {IEEE Transactions on Image Processing}, volume = {22}, year = {2013}, month = {09/2013}, pages = {3342 - 3352}, abstract = {

This article provides an alternative solution for the costly representation of multi-view video data, which can be used for both rendering and scene analysis. First, a new, efficient Monte Carlo discrete surface reconstruction method for foreground objects with static background is presented, which outperforms volumetric techniques and is suitable for GPU environments. Some extensions are also presented, which allow speeding up the reconstruction by exploiting multi-resolution and temporal correlation. Then, a fast meshing algorithm is applied, which allows interpolating a continuous surface from the discrete reconstructed points. As shown by the experimental results, the original video frames can be approximated with high accuracy by projecting the reconstructed foreground objects onto the original viewpoints. Furthermore, the reconstructed scene can be easily projected onto any desired virtual viewpoint, simplifying thus the design of Free-Viewpoint Video applications. In our experimental results, we show that our techniques for reconstruction and meshing compare favorably to the state-of-the-art, and we also introduce a rule-of-thumb for effective application of the method with a good quality vs. representation cost trade-off.

Note: ranked 53 among the 100 most downloaded IEEE Xplore articles in July 2013 (Gormish, M., "Top Downloads in IEEE Xplore [Reader{\textquoteright}s Choice]," IEEE Signal Processing Magazine, vol.31, no.1, pp.8,9, Jan. 2014. doi: 10.1109/MSP.2013.2282791)

}, doi = {10.1109/TIP.2013.2264818}, author = {Salvador, J. and Casas, J.} } @conference {cValero13, title = {Object recognition in urban hyperspectral images using binary partition tree representation}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS{\textquoteright}2013}, year = {2013}, publisher = {IEEE}, organization = {IEEE}, address = {Melbourne, Australia}, author = {Valero, S. and Salembier, P. and Chanussot, J.} } @conference {cAlonso-Gonzalez13, title = {PolSAR time series processing and analysis based on Binary Partition Trees}, booktitle = {PoLinSAR 2013 Workshop}, year = {2013}, address = {Frascati (Rome), Italy}, author = {Alonso-Gonz{\'a}lez, A. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P.} } @article {aAlonso-Gonzalez13, title = {Processing Multidimensional SAR and Hyperspectral Images With Binary Partition Tree}, journal = {Proceedings of the IEEE}, volume = {101}, year = {2013}, month = {March, 2013}, pages = {723 - 747}, chapter = {723 - 747}, abstract = {

The current increase of spatial as well as spectral resolutions of modern remote sensing sensors represents a real opportunity for many practical applications but also generates important challenges in terms of image processing. In particular, the spatial correlation between pixels and/or the spectral correlation between spectral bands of a given pixel cannot be ignored. The traditional pixel-based representation of images does not facilitate the handling of these correlations.

In this paper, we discuss the interest of a particular hierarchical region-based representation of images based on binary partition tree (BPT). This representation approach is very flexible as it can be applied to any type of image. Here both optical and radar images will be discussed. Moreover, once the image representation is computed, it can be used for many different applications. Filtering, segmentation, and classification will be detailed in this paper. In all cases, the interest of the BPT representation over the classical pixel-based representation will be highlighted.

}, doi = {10.1109/JPROC.2012.2205209}, author = {Alonso-Gonz{\'a}lez, A. and Valero, S. and Chanussot, J. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P.} } @article {aMolina11 , title = {Real-time user independent hand gesture recognition from time-of-flight camera video using static and dynamic models}, journal = {Machine vision and applications}, volume = {24}, year = {2013}, month = {08/2011}, pages = {187{\textendash}204}, chapter = {187}, abstract = {

The use of hand gestures offers an alternative to the commonly used human computer interfaces, providing a more intuitive way of navigating among menus and multimedia applications. This paper presents a system for hand gesture recognition devoted to control windows applications. Starting from the images captured by a time-of-flight camera (a camera that produces images with an intensity level inversely proportional to the depth of the objects observed) the system performs hand segmentation as well as a low-level extraction of potentially relevant features which are related to the morphological representation of the hand silhouette. Classification based on these features discriminates between a set of possible static hand postures which results, combined with the estimated motion pattern of the hand, in the recognition of dynamic hand gestures. The whole system works in real-time, allowing practical interaction between user and application.

}, issn = {0932-8092}, doi = {10.1007/s00138-011-0364-6}, url = {http://www.springerlink.com/content/062m51v58073572h/fulltext.pdf}, author = {Molina, J. and Escudero-Vi{\~n}olo, M. and Signorelo, A. and M. Pard{\`a}s and Ferran, C. and Bescos, J. and Marqu{\'e}s, F. and Mart{\'\i}nez, J.} } @article {aTochon13, title = {Segmentation hyperspectrales de forets tropicales par arbres de partition binaires}, journal = {Revue fran{\c c}aise de photogramm{\'e}trie et de t{\'e}l{\'e}d{\'e}tection}, volume = {202}, year = {2013}, month = {May 2013}, pages = {55-65}, author = {G. Tochon and J.B. Feret and Valero, S. and R.E. Martin and R. Tupayachi and Chanussot, J. and Salembier, P. and G. Asner} } @conference {cNiamut13, title = {Towards A Format-agnostic Approach for Production, Delivery and Rendering of Immersive Media}, booktitle = {ACM Multimedia Systems}, year = {2013}, month = {3/2013}, address = {Oslo, Norway}, abstract = {

The media industry is currently being pulled in the often-opposing directions of increased realism (high resolution, stereoscopic, large screen) and personalization (selection and control of content, availability on many devices). We investigate the feasibility of an end-to-end format-agnostic approach to support both these trends. In this paper, different aspects of a format- agnostic capture, production, delivery and rendering system are discussed. At the capture stage, the concept of layered scene representation is introduced, including panoramic video and 3D audio capture. At the analysis stage, a virtual director component is discussed that allows for automatic execution of cinematographic principles, using feature tracking and saliency detection. At the delivery stage, resolution-independent audiovisual transport mechanisms for both managed and unmanaged networks are treated. In the rendering stage, a rendering process that includes the manipulation of audiovisual content to match the connected display and loudspeaker properties is introduced. Different parts of the complete system are revisited demonstrating the requirements and the potential of this advanced concept.

}, author = {Niamut, O. and Kaiser, R. and Kienast, G. and Kochale, A. and Spille, J. and Schreer, O. and Ruiz-Hidalgo, J. and Macq, J. and Shirley, B.} } @conference {cPalou12, title = {2.1 Depth Estimation of Frames in Image Sequences Using Motion Occlusions}, booktitle = {Computer Vision {\textendash} ECCV 2012. Workshops and Demonstrations}, year = {2012}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, isbn = {978-3-642-33884-7}, doi = {10.1007/978-3-642-33885-4_52}, url = {http://dx.doi.org/10.1007/978-3-642-33885-4_52}, author = {Palou, G. and Salembier, P.} } @conference {cPalou12b, title = {Depth Ordering on Image Sequences Using Motion Occlusions}, booktitle = {IEEE Int. Conf. in Image Processing, ICIP 2012}, year = {2012}, month = {09/2012}, address = {Orlando, Florida, USA}, author = {Palou, G. and Salembier, P.} } @article {aCuadras12, title = {Distance-based measures of association with applications in relating hyperspectral images}, journal = {Communications in Statistics - Theory and Method}, volume = {41}, year = {2012}, pages = {2342{\textendash}2355}, abstract = {

We propose a distance-based method to relate two data sets. We define and study some measures of multivariate association based on distances between observations. The proposed approach can be used to deal with general data sets (e.g., observations on continuous, categorical or mixed variables). An application, using Hellinger distance, provides the relationships between two regions of hyperspectral images.

}, issn = {0361-0918}, doi = {10.1080/03610926.2012.654880}, author = {Cuadras, C. and Valero, S. and Cuadras, D. and Salembier, P. and Chanussot, J.} } @article {aAlonso-Gonzalez12, title = {Filtering and Segmentation of Polarimetric SAR Data Based on Binary Partition Trees}, journal = {IEEE transactions on geoscience and remote sensing}, volume = {50}, year = {2012}, pages = {593{\textendash}605}, abstract = {

In this paper,we propose the use of binary partition trees (BPT) to introduce a novel region-based and multi-scale polarimetric SAR (PolSAR) data representation. The BPT structure represents homogeneous regions in the data at different detail levels. The construction process of the BPT is based, firstly, on a region model able to represent the homogeneous areas, and, secondly, on a dissimilarity measure in order to identify similar areas and define the merging sequence. Depending on the final application, a BPT pruning strategy needs to be introduced. In this paper, we focus on the application of BPT PolSAR data representation for speckle noise filtering and data segmentation on the basis of the Gaussian hypothesis, where the average covariance or coherency matrices are considered as a region model. We introduce and quantitatively analyze different dissimilarity measures. In this case, and with the objective to be sensitive to the complete polarimetric information under the Gaussian hypothesis, dissimilarity measures considering the complete covariance or coherency matrices are employed. When confronted to PolSAR speckle filtering, two pruning strategies are detailed and evaluated. As presented, the BPT PolSAR speckle filter defined filters data according to the complete polarimetric information. As shown, this novel filtering approach is able to achieve very strong filtering while preserving the spatial resolution and the polarimetric information. Finally, the BPT representation structure is employed for high spatial resolution image segmentation applied to coastline detection. The analyses detailed in this work are based on simulated, as well as on real PolSAR data acquired by the ESAR system of DLR and the RADARSAT-2 system.

}, issn = {0196-2892}, doi = {10.1109/TGRS.2011.2160647}, author = {Alonso-Gonz{\'a}lez, A. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P.} } @inbook {bGallego12, title = {Foreground objects segmentation for moving camera scenarios based on SCGMM}, booktitle = {Computational Intelligence for Multimedia Understanding}, volume = {7252}, number = {Lecture Notes in Computer Science}, year = {2012}, month = {09/2011}, pages = {195-206}, publisher = {Springer}, organization = {Springer}, address = {Berlin Heidelberg}, abstract = {

In this paper we present a new system for segmenting non-rigid objects in moving camera sequences for indoor and outdoor scenarios that achieves a correct object segmentation via global MAP-MRF framework formulation for the foreground and background classification task. Our proposal, suitable for video indexation applications, receives as an input an initial segmentation of the object to segment and it consists of two region-based parametric probabilistic models to model the spatial (x,y) and color (r,g,b) domains of the foreground and background classes. Both classes rival each other in modeling the regions that appear within a dynamic region of interest that includes the foreground object to segment and also, the background regions that surrounds the object. The results presented in the paper show the correctness of the object segmentation, reducing false positive and false negative detections originated by the new background regions that appear near the region of the object.

}, keywords = {moving camera sequences, Object segmentation, SCGMM, video indexation}, issn = {978-3-642-32435-2}, doi = {10.1007/978-3-642-32436-9_17}, url = {http://www.springerlink.com/content/r6u266562h586476/}, author = {Gallego, J. and M. Pard{\`a}s and Solano, M.} } @conference {cPalou12a, title = {From local occlusion cues to global depth estimation}, booktitle = {IEEE Int. Conf. on Acoustics Speech and Signal Processing, ICASSP 2012}, year = {2012}, month = {03/2012}, address = {Kyoto, Japan}, author = {Palou, G. and Salembier, P.} } @article {aBosio12, title = {Gene Expression Data Classification Combining Hierarchical Representation and Efficient Feature Selection}, journal = {Journal of Biological Systems}, volume = {20}, year = {2012}, pages = {349-375}, abstract = {

A general framework for microarray data classification is proposed in this paper. It produces precise and reliable classifiers through a two-step approach. At first, the original feature set is enhanced by a new set of features called metagenes. These new features are obtained through a hierarchical clustering process on the original data. Two different metagene generation rules have been analyzed, called Treelets clustering and Euclidean clustering. Metagenes creation is attractive for several reasons: first, they can improve the classification since they broaden the available feature space and capture the common behavior of similar genes reducing the residual measurement noise. Furthermore, by analyzing some of the chosen metagenes for classification with gene set enrichment analysis algorithms, it is shown how metagenes can summarize the behavior of functionally related probe sets. Additionally, metagenes can point out, still undocumented, highly discriminant probe sets numerically related to other probes endowed with prior biological information in order to contribute to the knowledge discovery process.

The second step of the framework is the feature selection which applies the Improved Sequential Floating Forward Selection algorithm (IFFS) to properly choose a subset from the available feature set for classification composed of genes and metagenes. Considering the microarray sample scarcity problem, besides the classical error rate, a reliability measure is introduced to improve the feature selection process. Different scoring schemes are studied to choose the best one using both error rate and reliability. The Linear Discriminant Analysis classifier (LDA) has been used throughout this work, due to its good characteristics, but the proposed framework can be used with almost any classifier. The potential of the proposed framework has been evaluated analyzing all the publicly available datasets offered by the Micro Array Quality Control Study, phase II (MAQC). The comparative results showed that the proposed framework can compete with a wide variety of state of the art alternatives and it can obtain the best mean performance if a particular setup is chosen. A Monte Carlo simulation confirmed that the proposed framework obtains stable and repeatable results.

}, doi = {10.1142/S0218339012400025}, url = {http://www.worldscientific.com/doi/abs/10.1142/S0218339012400025}, author = {Bosio, M. and P. Bellot and Salembier, P. and Albert Oliveras} } @article {bSuau12, title = {INTAIRACT: Joint Hand Gesture and Fingertip Classification for Touchless Interaction}, journal = {Lecture notes in computer science}, volume = {7585}, year = {2012}, month = {10/2012}, pages = {602-606}, publisher = {Springer}, chapter = {3}, address = {Heidelberg}, abstract = {

In this demo we present INTAIRACT, an online hand-based touchless interaction system. Interactions are based on easy-to-learn hand gestures, that combined with translations and rotations render a user friendly and highly configurable system. The main advantage with respect to existing approaches is that we are able to robustly locate and identify fingertips. Hence, we are able to employ a simple but powerful alphabet of gestures not only by determining the number of visible fingers in a gesture, but also which fingers are being observed. To achieve such a system we propose a novel method that jointly infers hand gestures and fingertip locations using a single depth image from a consumer depth camera. Our approach is based on a novel descriptor for depth data, the Oriented Radial Distribution (ORD) [1]. On the one hand, we exploit the ORD for robust classification of hand gestures by means of efficient k-NN retrieval. On the other hand, maxima of the ORD are used to perform structured inference of fingertip locations. The proposed method outperforms other state-of-the-art approaches both in gesture recognition and fingertip localization. An implementation of the ORD extraction on a GPU yields a real-time demo running at approximately 17fps on a single laptop.

1. Suau, X., Ruiz-Hidalgo, J., Casas, J.R.: Oriented Radial Distribution on Depth\ Data: Application to the Detection of End-Effectors. In: ICASSP. (2012)

}, isbn = {978-3-642-33885-4}, issn = {978-3-642-33884-7}, doi = {10.1007/978-3-642-33885-4_62}, author = {Suau, X. and Alcoverro, M. and L{\'o}pez-M{\'e}ndez, A. and Ruiz-Hidalgo, J. and Casas, J.} } @conference {cBosio12, title = {Microarray classification with hierarchical data representation and novel feature selection criteria}, booktitle = {IEEE 12th International Conference on BioInformatics and BioEngineering}, year = {2012}, month = {11/2012}, address = {Larnaca, Cyprus}, author = {Bosio, M. and P. Bellot and Salembier, P. and Albert Oliveras} } @conference {cBosio12a, title = {Multiclass cancer microarray classification algorithm with Pair-Against-All redundancy}, booktitle = {The 2012 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS{\textquoteright}12)}, year = {2012}, month = {12/2012}, address = {Washington, DC, USA}, author = {Bosio, M. and P. Bellot and Salembier, P. and Albert Oliveras} } @conference {cSuau12, title = {Oriented radial distribution on depth data: Application to the detection of end-effectors}, booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing}, year = {2012}, month = {03/2012}, address = {Kyoto, Japan}, abstract = {

End-effectors are considered to be the main topological extremities of a given 3D body. Even if the nature of such body is not restricted, this paper focuses on the human body case. Detection of human extremities is a key issue in the human motion capture domain, being needed to initialize and update the tracker. Therefore, the effectiveness of human motion capture systems usually depends on the reliability of the obtained end-effectors. The increasing accuracy, low cost and easy installation of depth cameras has opened the door to new strategies to overcome the body pose estimation problem. With the objective of detecting the head, hands and feet of a human body, we propose a new local feature computed from depth data, which gives an idea of its curvature and prominence. Such feature is weighted depending on recent detections, providing also a temporal dimension. Based on this feature, some end-effector candidate blobs are obtained and classified into head, hands and feet according to three probabilistic descriptors.

}, doi = {10.1109/ICASSP.2012.6288002}, author = {Suau, X. and Ruiz-Hidalgo, J. and Casas, J.} } @article {aSuau12, title = {Real-time head and hand tracking based on 2.5D data}, journal = {IEEE Transactions on Multimedia }, volume = {14}, year = {2012}, month = {06/2012}, pages = {575-585 }, abstract = {

A novel real-time algorithm for head and hand tracking is proposed in this paper. This approach is based on data from a range camera, which is exploited to resolve ambiguities and overlaps. The position of the head is estimated with a depth-based template matching, its robustness being reinforced with an adaptive search zone. Hands are detected in a bounding box attached to the head estimate, so that the user may move freely in the scene. A simple method to decide whether the hands are open or closed is also included in the proposal. Experimental results show high robustness against partial occlusions and fast movements. Accurate hand trajectories may be extracted from the estimated hand positions, and may be used for interactive applications as well as for gesture classification purposes.

}, issn = {1520-9210}, doi = {http://dx.doi.org/10.1109/TMM.2012.2189853}, author = {Suau, X. and Ruiz-Hidalgo, J. and Casas, J.} } @conference {cJimenez12, title = {Registration of Multi-Modal Neuroimaging Datasets by Considering the Non-Overlapping Field of View into the NMI Calculation}, booktitle = {IEEE International Symposium on Biomedical Imaging, ISBI 2012}, year = {2012}, address = {Barcelona, Spain}, author = {Jim{\'e}nez, X and Figueiras, F and Marqu{\'e}s, F. and Salembier, P. and Herance, R and Rojas, S and Mill{\'a}n, O and Pareto, D and Domingo Gispert, J} } @conference {cAlonso-Gonzalez12a, title = {Temporal polsar image series exploitation with binary partition trees}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012}, year = {2012}, address = {Munich, Germany}, author = {Alonso-Gonz{\'a}lez, A. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P.} } @conference {cAlonso-Gonzalez12, title = {Variable local weight filtering for polsar data speckle noise reduction}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS{\textquoteright}2012}, year = {2012}, address = {Munich, Germany}, author = {Alonso-Gonz{\'a}lez, A. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P.} } @conference {cSalvador12, title = {Variational Reconstruction and Restoration for Video Super-Resolution}, booktitle = {International Conference on Pattern Recognition (ICPR)}, year = {2012}, month = {11-2012}, address = {Tsukuba, Japan}, abstract = {

This paper presents a variational framework for obtaining super-resolved video-sequences, based on the observation that reconstruction-based Super-Resolution (SR) algorithms are limited by two factors: registration exactitude and Point Spread Function (PSF) estimation accuracy.\ To minimize the impact of the first limiting factor, a small-scale linear inpainting algorithm is proposed to provide smooth SR video frames.\ To improve the second limiting factor, a fast PSF local estimation and total variation-based denoising is proposed. Experimental results reflect the improvements provided by the proposed method when compared to classic SR approaches.

}, url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=\&arnumber=6460315\&contentType=Conference+Publications\&searchField\%3DSearch_All\%26queryText\%3Dvariational+reconstruction}, author = {Salvador, J. and Rivero, D. and Kochale, A. and Ruiz-Hidalgo, J.} } @article {aButko11, title = {Acoustic event detection based on feature-level fusion of audio and video modalities}, journal = {Eurasip journal on advances in signal processing}, volume = {2011}, year = {2011}, pages = {1{\textendash}11}, abstract = {

Acoustic event detection (AED) aims at determining the identity of sounds and their temporal position in audio signals. When applied to spontaneously generated acoustic events, AED based only on audio information shows a large amount of errors, which are mostly due to temporal overlaps. Actually, temporal overlaps accounted for more than 70\% of errors in the real-world interactive seminar recordings used in CLEAR 2007 evaluations. In this paper, we improve the recognition rate of acoustic events using information from both audio and video modalities. First, the acoustic data are processed to obtain both a set of spectrotemporal features and the 3D localization coordinates of the sound source. Second, a number of features are extracted from video recordings by means of object detection, motion analysis, and multicamera person tracking to represent the visual counterpart of several acoustic events. A feature-level fusion strategy is used, and a parallel structure of binary HMM-based detectors is employed in our work. The experimental results show that information from both the microphone array and video cameras is useful to improve the detection rate of isolated as well as spontaneously generated acoustic events.

}, issn = {1687-6172}, doi = {10.1155/2011/485738}, url = {http://www.hindawi.com/journals/asp/2011/485738/}, author = {Butko, T. and Cristian Canton-Ferrer and Segura, C. and Xavier Gir{\'o}-i-Nieto and Nadeu, C. and Hernando, J. and Casas, J.} } @conference {cValero11a, title = {Arbre de partition binaire: un nouvel outil pour la repr{\'e}sentation hi{\'e}rarchique et l{\textquoteright}analyse des images hyperspectrales}, booktitle = {XXIII{\`e} Colloque sur le Traitement du Signal et des Images, GRETSI 2011}, year = {2011}, pages = {120{\textendash}125}, address = {Bordeaux, France}, url = {http://hdl.handle.net/2117/14621}, author = {Valero, S. and Salembier, P. and Chanussot, J.} } @conference {cAlonso-Gonzalez11a, title = {Binary partition tree as a polarimetric SAR data representation in the space-time domain}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011}, year = {2011}, pages = {3819{\textendash}3822}, address = {Vanouver, Canada}, isbn = {978-1-4577-1005-6}, doi = {10.1109/IGARSS.2011.6050063}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6050063}, author = {Alonso-Gonz{\'a}lez, A. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P.} } @conference {cSalvador11, title = {A compact 3D representation for multi-view video}, booktitle = {2011 International Conference on 3D Imaging}, year = {2011}, pages = {1{\textendash}8}, abstract = {

This paper presents a methodology for obtaining a 3D reconstruction of a dynamic scene in multi-camera settings. Our target is to derive a compact representation of the 3D scene which is effective and accurate, whatever the number of cameras and even for very-wide baseline settings. Easing realtime 3D scene capture has outstanding applications in 2D and 3D content production, free viewpoint video of natural scenes and interactive video applications.\ 

The method proposed here has several original contributions on how to accelerate the process: it exploits spatial and temporal consistency for speeding up reconstruction, dividing the problem in two parts. First, 3D surfaces are efficiently sampled to obtain a silhouette-consistent set of colored surface points and normals, using a novel algorithm presented in this paper. Then, a fast, greedy meshing algorithm retrieves topologically correct continuous surfaces from the dense sets of oriented points, providing a suitable representation for multi-view video.\ 

Compared to other techniques in the literature, the presented approach is capable of retrieving 3D surfaces of foreground objects in real-time by exploiting the computing capabilities of GPUs. This is feasible due to the parallelized design of the surface sampling algorithm. The reconstructed surfaces can effectively be used for interactive representations.\ 

The presented methodology also offers good scalability to large multi-view video settings.

}, isbn = {978-1-61284-349-0}, doi = {10.1109/IC3D.2011.6584371}, url = {http://www.3dstereomedia.eu}, author = {Salvador, J. and Casas, J.} } @article {aTello11, title = {Edge enhancement algorithm based on the wavelet transform for automatic edge detection in SAR images}, journal = {IEEE transactions on geoscience and remote sensing}, volume = {49}, number = {1}, year = {2011}, pages = {222{\textendash}235}, issn = {0196-2892}, doi = {10.1109/TGRS.2010.2052814}, url = {http://hdl.handle.net/2117/11057}, author = {Tello, M. and L{\'o}pez-Mart{\'\i}nez, C. and Mallorqui, J.J. and Salembier, P.} } @conference {cBosio11, title = {Feature set enhancement via hierarchical clustering for microarray classification}, booktitle = {IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2011}, year = {2011}, month = {dec.}, pages = {226 -229}, abstract = {

A new method for gene expression classification is proposed in this paper. In a first step, the original feature set is enriched by including new features, called metagenes, produced via hierarchical clustering. In a second step, a reliable classifier is built from a wrapper feature selection process. The selection relies on two criteria: the classical classification error rate and a new reliability measure. As a result, a classifier with good predictive ability using as few features as possible to reduce the risk of overfitting is obtained. This method has been tested on three public cancer datasets: leukemia, lymphoma and colon. The proposed method has obtained interesting classification results and the experiments have confirmed the utility of both metagenes and feature ranking criterion to improve the final classifier.

}, keywords = {cancer, classical classification error rate, classifier, colon, feature set enhancement, gene expression classification, hierarchical clustering, leukemia, lymphoma, medical computing, metagenes, microarray classification, overfitting risk reduction, pattern classification, pattern clustering, public cancer datasets, reliability measure, wrapper feature selection process}, doi = {10.1109/GENSiPS.2011.6169486}, author = {Bosio, M. and P. Bellot and Salembier, P. and Albert Oliveras} } @conference {cSchreer11, title = {Format-agnostic approach for production, delivery and rendering of immersive media}, booktitle = {Networked and Electronic Media Summit}, year = {2011}, pages = {{\textendash}}, isbn = {SN}, url = {http://nem-summit.eu/program/}, author = {Schreer, O. and Thomas, G. and Niamut, O. and Macq, J. and Kochale, A. and Batke, J. and Ruiz-Hidalgo, J. and Oldfield, R. and Shirley, B. and Thallinger, G.} } @conference {cBenediktsson11, title = {Hierarchical analysis of remote sensing data: morphological attribute profiles and binary partition trees}, booktitle = {International Symposium on Mathematical Morphology 2011}, year = {2011}, pages = {306{\textendash}319}, address = {Intra, Lake Maggiore, Italy}, isbn = {3642215688}, doi = {10.1007/978-3-642-21569-8_27}, url = {http://hdl.handle.net/2117/14624}, author = {Benediktsson, J. and Bruzzone, L. and Chanussot, J. and Dalla Mura, M. and Salembier, P. and Valero, S.} } @phdthesis {dValero11, title = {Hyperspectral image representation and Processing with Binary Partition Trees}, year = {2011}, school = {Universitat Polit{\`e}cnica de Catalunya (UPC)}, type = {phd}, abstract = {

The optimal exploitation of the information provided by hyperspectral images requires the development of advanced image processing tools. Therefore, this PhD thesis proposes the construction and the processing of a new region-based hierarchical hyperspectral image representation: the Binary Partition Tree (BPT). This representation can be interpreted as a set of hierarchical regions stored in a tree structure. Based on region-merging techniques, the construction of BPT is investigated in this work by studying hyperspectral region models and the associated similarity metrics. Once the BPT is constructed,the fixed tree structure allows implementing efficient and advanced application-dependent techniques on it. The application-dependent processing of BPT is generally implemented through a specific pruning of the tree. Accordingly, some pruning techniques are proposed and discussed according to different applications. This Ph.D is focused in particular on segmentation, object detection and classification of hyperspectral imagery. Experimental results on various hyper spectral data sets demonstrate the interest and the good performances of the BPT representation.

}, url = {http://www.gipsa-lab.grenoble-inp.fr/formation/theses-soutenues.php?id_these=572}, author = {Valero, S.}, editor = {Salembier, P.} } @conference {cValero11b, title = {Hyperspectral image segmentation using binary partition trees}, booktitle = {IEEE International Conference on Image Processing, ICIP 2011}, year = {2011}, pages = {1273{\textendash}1276}, address = {Brussels, Belgium}, isbn = {0-7803-5470-2}, doi = {10.1109/ICIP.2011.6115666}, url = {http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6094293}, author = {Valero, S. and Salembier, P. and Chanussot, J.} } @conference {cBragos11a, title = {Implementation and first results of the Introduction to Engineering course in the ETSETB-UPC new degrees}, booktitle = {II Conferencia Internacional en Fomento e Innovaci{\'o}n con Nuevas Tecnolog{\'\i}as en la Docencia de la Ingenier{\'\i}a}, year = {2011}, pages = {1{\textendash}4}, isbn = {978-1-4577-0559-5}, doi = {10.1109/FINTDI.2011.5945971}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5945971}, author = {Bragos, R. and Pegueroles, J. and Alarc{\'o}n, E. and Camps, A. and Sarda, J. and Consolacion, C. and Mussons, J. and Pons, O. and Albert Oliveras and Garc{\'\i}a, M. and Onrubia, R. and Elisa Sayrol} } @conference {cValero11, title = {Improved binary partition tree construction for hyperspectral images: application to object detection}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011}, year = {2011}, pages = {2515{\textendash}2518}, address = {Vancouver, Canada}, doi = {10.1109/IGARSS.2011.6049723}, url = {http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6034618}, author = {Valero, S. and Salembier, P. and Chanussot, J. and Cuadres, C.} } @conference {cGallego11, title = {Joint multi-view foreground segmentation and 3D reconstruction with tolerance loop}, booktitle = {IEEE International Conference on Image Processing}, year = {2011}, pages = {997{\textendash}1000}, abstract = {

In this paper we present a novel foreground segmentation and 3D reconstruction system for multi-view scenarios. The system achieves correct 3D object reconstruction even when foreground segmentation presents critical misses in some of the views. We introduce the spatial redundancy of the multi-view data into the foreground segmentation process by combining segmentation and the 3D reconstruction in a two steps workflow. First, the segmentation of the objects in each view uses a monocular, region-based foreground segmentation in a MAP-MRF framework for foreground, background and shadow classes. Next, we compute an iterative volume reconstruction in a 3D tolerance loop, obtaining an iteratively enhanced SfS volume. Foreground segmentation is improved by updating the foreground model of each view at each iteration. The results presented in this paper show the improved foreground segmentation and the reduction of errors in the reconstruction of the volume.

}, isbn = {978-1-4577-1304-0}, doi = {10.1109/ICIP.2011.6116731}, url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\&arnumber=6116731}, author = {Gallego, J. and Salvador, J. and Casas, J. and M. Pard{\`a}s} } @conference {cAlarcon11, title = {Learning to conceive, design, implement and operate circuits and systems}, booktitle = {2011 IEEE International Symposium on Circuits and Systems}, year = {2011}, pages = {1183{\textendash}1186}, isbn = {978-1-4244-9472-9}, doi = {10.1109/ISCAS.2011.5937780}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5937780\&tag=1}, author = {Alarc{\'o}n, E. and Bragos, R. and Elisa Sayrol} } @article {dPalou11, title = {Monocular Depth Ordering Using Occlusion Cues}, year = {2011}, institution = {Technical University of Catalonia}, type = {masters}, address = {Barcelona}, author = {Palou, G. and Salembier, P.} } @inbook {bDigne11, title = {Neighborhood Filters and the Recovery of 3D Information}, booktitle = {Handbook of Mathematical Methods in Imaging}, year = {2011}, pages = {1203-1229}, publisher = {Springer Verlag}, organization = {Springer Verlag}, isbn = {978-0-387-92919-4}, author = {J. Digne and Dimiccoli, M. and Salembier, P. and N. Sabater} } @conference {cPalou11, title = {Occlusion-based depth ordering on monocular images with binary partition tree}, booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2011}, year = {2011}, pages = {1093{\textendash}1096}, address = {Prague, Czech Republic}, doi = {0.1109/ICASSP.2011.5946598}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5946598\&tag=1}, author = {Palou, G. and Salembier, P.} } @conference {cAlonso-Gonzalez11, title = {PolSAR speckle filtering and segmentation based on binary partition tree representation}, booktitle = {5th International Workshop on Science and Applications of SAR Polarimetry and Polarimetric Interferometry, PolInSAR 2011}, year = {2011}, pages = {1{\textendash}19}, address = {Frascati (Rome), Italy}, url = {http://cataleg.upc.edu/record=b1233548~S1*cat}, author = {Alonso-Gonz{\'a}lez, A. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P.} } @conference {cSuau11, title = {Real-time head and hand tracking based on 2.5D data}, booktitle = {ICME - 2011 IEEE International Conference on Multimedia and Expo}, year = {2011}, pages = {1{\textendash}6}, abstract = {

A novel real-time algorithm for head and hand tracking is proposed in this paper. This approach is based on 2.5D data from a range camera, which is exploited to resolve ambiguities and overlaps. Experimental results show high robustness against partial occlusions and fast movements. The estimated positions are fairly stable, allowing the extraction of accurate trajectories which may be used for gesture classification purposes.

}, isbn = {975001880X}, doi = {10.1109/ICME.2011.6011869}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6011869\&tag=1}, author = {Suau, X. and Casas, J. and Ruiz-Hidalgo, J.} } @phdthesis {dSalvador11, title = {Surface Reconstruction for Multi-View Video}, year = {2011}, school = {Universitat Polit{\`e}cnica de Catalunya (UPC)}, type = {phd}, abstract = {

This thesis introduces a methodology for obtaining an alternative representation of video sequences captured by calibrated multi-camera systems in controlled environments with known scene background. This representation consists in a 3D description of the surfaces of foreground objects, which allows for the recovering of part of the 3D information of the original scene lost in the projection process in each camera.

The choice of the type of representation and the design of the reconstruction techniques are driven by three requirements that appear in smart rooms or recording studios. In these scenarios, video sequences captured by a multi-camera rig are used both for analysis applications and interactive visualization methods. The requirements are: the reconstruction method must be fast in order to be usable in interactive applications, the surface representation must provide a compression of the multi-view data redundancies and this representation must also provide all the relevant information to be used for analysis applications as well as for free-viewpoint video.

Once foreground and background are segregated for each view, the reconstruction process is divided in two stages. The first one obtains a sampling of the foreground surfaces (including orientation and texture), whereas the second provides closed, continuous surfaces from the samples, through interpolation.

The sampling process is interpreted as a search for 3D positions that result in feature matchings between different views. This search process can be driven by different mechanisms: an image-based approach, another one based on the deformation of a surface from frame to frame or a statistical sampling approach where samples are searched around the positions of other detected samples, which is the fastest and easiest to parallelize of the three approaches.

A meshing algorithm is also presented, which allows for the interpolation of surfaces between samples. Starting by an initial triangle, which connects three points coherently oriented, an iterative expansion of the surface over the complete set of samples takes place. The proposed method presents a very accurate reconstruction and results in a correct topology. Furthermore, it is fast enough to be used interactively.

The presented methodology for surface reconstruction permits obtaining a fast, compressed and complete representation of foreground elements in multi-view video, as reflected by the experimental results.

}, url = {http://hdl.handle.net/10803/108907}, author = {Salvador, J.}, editor = {Casas, J.} } @conference {cValero10a, title = {Comparison of merging orders and pruning strategies for binary partition tree in hyperspectral data}, booktitle = {IEEE International Conference on Image Processing, ICIP 2010}, year = {2010}, pages = {2565{\textendash}2568}, address = {Hong Kong, China}, doi = {10.1109/ICIP.2010.5652595}, url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\&arnumber=5652595}, author = {Valero, S. and Salembier, P. and Chanussot, J.} } @inbook {bMarcotegui10a, title = {Compression}, booktitle = {Morphologie Math{\'e}matique II: estimation choix et mise en oeuvre}, year = {2010}, publisher = {Hermes, Lavoisier}, organization = {Hermes, Lavoisier}, edition = {L. Najman and H. Talbot (Eds.)}, isbn = {978-2-7462-2593-0}, url = {http://cataleg.upc.edu/search~S1*cat/X?estimation\%2C+choix\&SORT=D\&searchscope=1}, author = {Marcotegui, B. and Salembier, P.} } @inbook {bMarcotegui10, title = {Compression}, booktitle = {Mathematical morphology from theories to applications}, year = {2010}, pages = {385{\textendash}391}, publisher = {Wiley}, organization = {Wiley}, edition = {L. Najman and H. Talbot (Eds.)}, chapter = {16}, isbn = {978-1848212152}, url = {http://cataleg.upc.edu/record=b1376601~S1*cat}, author = {Marcotegui, B. and Salembier, P.} } @inbook {bWaibel10, title = {Computers in the Human Interaction Loop}, booktitle = {Handbook on Ambient Intelligence and Smart Environments (AISE)}, year = {2010}, pages = {1071{\textendash}1116}, publisher = {Springer}, organization = {Springer}, address = {Boston, MA}, abstract = {

It is a common experience in our modern world, for us humans to be overwhelmed by the complexities of technological artifacts around us, and by the attention they demand. While technology provides wonderful support and helpful assistance, it also causes an increased preoccupation with technology itself and a related fragmentation of attention. But as humans, we would rather attend to a meaningful dialog and interaction with other humans, than to control the operations of machines that serve us. The cause for such complexity and distraction, however, is a natural consequence of the flexibility and choice of functions and features that technology has to offer. Thus flexibility of choice and the availability of desirable functions are in conflict with ease of use and our very ability to enjoy their benefits.\ 

}, isbn = {978-0-387-93807-3}, doi = {10.1007/978-0-387-93808-0_40}, author = {Waibel, A. and Stiefelhagen, R. and Carlson, R. and Casas, J. and Kleindienst, J. and Lamel, L. and Lanz, O. and Mostefa, D. and Omologo, M. and Pianesi, F. and Polymenakos, L. and Potamianos, G. and Soldatos, J. and Sutschet, G. and Terken, J.} } @inbook {bSalembier10, title = {Connected operators based on tree pruning strategies}, booktitle = {Mathematical morphology from theories to applications}, year = {2010}, publisher = {Wiley}, organization = {Wiley}, edition = {L. Najman and H. Talbot (Eds.)}, chapter = {7}, isbn = {978-1848212152}, url = {http://cataleg.upc.edu/record=b1376601~S1*cat}, author = {Salembier, P.} } @conference {cGiro-i-Nieto10, title = {Digimatge, a Rich Internet Application for video retrieval from a Multimedia Asset Management system}, booktitle = {11th ACM SIGMM International Conference on Multimedia Information Retrieval}, year = {2010}, abstract = {

This paper describes the integration of two new services aimed at assisting into the retrieval of video content from an existing Multimedia Asset Manager (MAM) of a TV broadcaster archive. The first tool suggests tags after a first textual query, and the second ranks the keyframe of retrieved assets according to their visual similarity. Both applications were integrated as web services that are accessed from a Rich Internet Application via REST calls.

}, isbn = {978-1-60558-815-5}, doi = {10.1145/1743384.1743458}, url = {http://upcommons.upc.edu/e-prints/urlFiles?idDrac=2249267}, author = {Xavier Gir{\'o}-i-Nieto and Salla, R. and Vives, X.} } @conference {cAlonso-Gonzalez10, title = {Filtering and segmentation of polarimetric SAR images with binary partition trees}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010}, year = {2010}, pages = {4043{\textendash}4046}, address = {Honolulu, USA}, isbn = {978-1-4244-9564-1}, doi = {10.1109/IGARSS.2010.5653466}, url = {http://cataleg.upc.edu/record=b1167223~S1*cat}, author = {Alonso-Gonz{\'a}lez, A. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P.} } @conference {cSalvador10b, title = {From silhouettes to 3D points to mesh: towards free viewpoint video}, booktitle = {ACM Workshop on 3D Video Processing (3DVP)}, year = {2010}, pages = {19{\textendash}24}, isbn = {1522-4880}, doi = {10.1145/1877791.1877797}, url = {http://delivery.acm.org/10.1145/1880000/1877797/p19-salvador.pdf?ip=147.83.95.37\&CFID=24773176\&CFTOKEN=26981598\&__acm__=1306838718_5a07df5f539bac704e3bc98a25b9a68c}, author = {Salvador, J. and Suau, X. and Casas, J.} } @phdthesis {dRolon10, title = {Generalized Lifting for Sparse Image Representation and Coding}, year = {2010}, school = {Universitat Polit{\`e}cnica de Catalunya (UPC)}, type = {phd}, author = {Rol{\'o}n, J.}, editor = {Salembier, P.} } @article {aGudmundsson10, title = {Improved 3D reconstruction in smart-room environments using ToF imaging}, journal = {Computer vision and image understanding}, volume = {114}, number = {12}, year = {2010}, month = {12/2010}, pages = {1376{\textendash}1384}, abstract = {

This paper presents a general analysis framework towards exploiting the underlying hierarchical and scalable structure of an articulated object for pose estimation and tracking. Scalable human body models are introduced as an ordered set of articulated models fulfilling an inclusive hierarchy. The concept of annealing is applied to derive a generic particle filtering scheme able to perform a sequential filtering over the set of models contained in the scalable human body model. Two annealing loops are employed, the standard likelihood annealing and the newly introduced structural annealing, leading to a robust, progressive and efficient analysis of the input data. The validity of this scheme is tested by performing markerless human motion capture in a multi-camera environment employing the standard HumanEva annotated datasets. Finally, quantitative results are presented and compared with other existing HMC techniques.

}, issn = {1077-3142}, doi = {10.1016/j.cviu.2010.07.011}, url = {http://www.sciencedirect.com/science/article/pii/S1077314210001736}, author = {Gudmundsson, S. and M. Pard{\`a}s and Casas, J. and Sveinsson, J. and Aanaes, H. and Larsen, R.} } @conference {cRolon10, title = {Improved local pdf estimation in the wavelet domain for generalized lifting}, booktitle = {Picture Coding Symposium, PCS 2010}, year = {2010}, address = {Nagoya, Japan}, isbn = {0-7803-3192-3}, url = {http://hdl.handle.net/2117/11675}, author = {Rol{\'o}n, J. and Salembier, P.} } @conference {cSalvador10, title = {Joint estimation of shape and motion from silhouettes}, booktitle = {2010 IEEE International Conference on Image Processing}, year = {2010}, pages = {4069{\textendash}4072}, isbn = {3-540-66082-8}, doi = {10.1109/ICIP.2010.5654022}, url = {http://www.cic.unb.br/~mylene/PI_2010_2/ICIP10/pdfs/0004069.pdf}, author = {Salvador, J. and Casas, J.} } @article {cSayrol10, title = {Mixed integration of CDIO skills into telecommunication engineering curricula}, journal = {Elektronika ir elektrotechnika}, volume = {102}, number = {102}, year = {2010}, pages = {127{\textendash}130}, issn = {1392-1215}, url = {http://www.ktu.lt/lt/mokslas/zurnalai/elektros_z/z102/32__ISSN_1392-1215_Mixed\%20Integration\%20of\%20CDIO\%20skills\%20into\%20Telecommunication\%20Engineering\%20Curricula.pdf}, author = {Elisa Sayrol and Bragos, R. and Alarc{\'o}n, E. and Cabrera, M. and Calveras, A. and Comellas, J. and O{\textquoteright}Callaghan, J. and Pegueroles, J. and Pla, E. and Prat, L. and Saez, G. and Sarda, J. and Tallon, C.} } @article {aGudmundsson10a, title = {Model-based hand gesture tracking in ToF image sequences}, journal = {Lecture notes in computer science}, volume = {6169/2010}, year = {2010}, pages = {118{\textendash}127}, issn = {0302-9743}, doi = {10.1007/978-3-642-14061-7_12}, url = {http://www.springerlink.com/content/l1117675tv565twq/}, author = {Gudmundsson, S. and Sveinsson, J. and M. Pard{\`a}s and Aanaes, H. and Larsen, R.} } @conference {cValero10, title = {New hyperspectral data representation using binary partition tree}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010}, year = {2010}, pages = {80{\textendash}83}, address = {Honolulu, USA}, isbn = {978-1-4244-4761-9}, doi = {10.1109/IGARSS.2010.5649780}, url = {http://hdl.handle.net/2117/11005}, author = {Valero, S. and Salembier, P. and Chanussot, J.} } @conference {cSalvador10a, title = {Photo-consistent surfaces from a sparse set of viewpoints}, booktitle = {2010 IEEE International Conference on Image Processing}, year = {2010}, pages = {4045{\textendash}4048}, isbn = {978-1-4244-5655-6}, doi = {10.1109/ICIP.2010.5649006}, url = {http://www.cic.unb.br/~mylene/PI_2010_2/ICIP10/pdfs/0004045.pdf}, author = {Salvador, J. and Casas, J.} } @conference {cBragos10, title = {Proceso de inversi{\'o}n de competencias gen{\'e}ricas en los nuevos planes de estudios de grado de la ETSETB de acuerdo con el modelo CDIO}, booktitle = {IX Congreso de Tecnolog{\'\i}as Aplicadas a la Ense{\~n}anza de la Electr{\'o}nica}, year = {2010}, pages = {1{\textendash}9}, isbn = {978-84-96737-68-6}, url = {http://upcommons.upc.edu/e-prints/urlFiles?idDrac=4451103}, author = {Bragos, R. and Alarc{\'o}n, E. and Cabrera, M. and Calveras, A. and Comellas, J. and O{\textquoteright}Callaghan, J. and Pegueroles, J. and Prat, L. and Saez, G. and Sarda, J. and Elisa Sayrol} } @conference {cCuadras10, title = {Some measures of multivariate association relating two spectral data sets}, booktitle = {19th International Conference on Computational Statistics, COMSTAT 2010}, year = {2010}, address = {Paris, France}, author = {Cuadras, C. and Valero, S. and Salembier, P. and Chanussot, J.} } @conference {cSuau10, title = {Surface reconstruction by restricted and oriented propagation}, booktitle = {2010 IEEE International Conference on Image Processing}, year = {2010}, pages = {813{\textendash}816}, isbn = {952-15-1364-0}, doi = {10.1109/ICIP.2010.5652707}, author = {Suau, X. and Casas, J. and Ruiz-Hidalgo, J.} } @inbook {bNickel09, title = {Activity Classification}, booktitle = {Computers in the Human Interaction Loop}, year = {2009}, pages = {107{\textendash}119}, publisher = {Springer}, organization = {Springer}, address = {London}, abstract = {

When a person enters a room, he or she immediately develops a mental concept about {\textquotedblleft}what is going on{\textquotedblright} in the room; for example, people may be working in the room, people may be engaged in a conversation, or the room may be empty. The CHIL services depend on just the same kind of semantic description, which is termed activity in the following. The {\textquotedblleft}Connector{\textquotedblright} or the {\textquotedblleft}Memory Jog{\textquotedblright}, for example, could provide support that is appropriate for the given context if it knew about the current activity at the user{\textquoteright}s place. This kind of higher-level understanding of human interaction processes could then be used, e.g., for rating the user{\textquoteright}s current availability in a certain situation.

}, isbn = {978-1-84882-053-1}, doi = {10.1007/978-1-84882-054-8}, url = {http://www.springerlink.com/content/tj2x827107563616/}, author = {Nickel, K. and M. Pard{\`a}s and Stiefelhagen, R. and Cristian Canton-Ferrer and Landabaso, J. and Casas, J.} } @mastersthesis {xRovira09, title = {Aplicaci{\'o} rica d{\textquoteright}internet per a la consulta amb text i imatge a la Corporaci{\'o} Catalana de Mitjans Audiovisuals}, year = {2009}, abstract = {

Premi millor projecte final de carrera d{\textquoteright}Enginyeria de Telecomunicaci{\'o} en Serveis Telem{\`a}tics. Atorgat per Accenture (Curs 2009-2010)

}, url = {http://hdl.handle.net/2099.1/8766}, author = {Salla-Rovira, Ramon}, editor = {Xavier Gir{\'o}-i-Nieto and Vives, X.} } @conference {cCanton-Ferrer09, title = {Audiovisual Event Detection Towards Scene Understanding}, booktitle = {2009 IEEE Computer-Society Conference on Computer Vision and Pattern Recognition Workshops}, year = {2009}, pages = {840{\textendash}847}, abstract = {

Acoustic events produced in meeting environments may contain useful information for perceptually aware interfaces and multimodal behavior analysis. In this paper, a system to detect and recognize these events from a multimodal perspective is presented combining information from multiple cameras and microphones. First, spectral and temporal features are extracted from a single audio channel and spatial localization is achieved by exploiting cross-correlation among microphone arrays. Second, several video cues obtained from multi-person tracking, motion analysis, face recognition, and object detection provide the visual counterpart of the acoustic events to be detected. A multimodal data fusion at score level is carried out using two approaches: weighted mean average and fuzzy integral. Finally, a multimodal database containing a rich variety of acoustic events has been recorded including manual annotations of the data. A set of metrics allow assessing the performance of the presented algorithms. This dataset is made publicly available for research purposes.

}, doi = {10.1109/CVPRW.2009.5204264}, author = {Cristian Canton-Ferrer and Butko, T. and Segura, C. and Xavier Gir{\'o}-i-Nieto and Nadeu, C. and Hernando, J. and Casas, J.} } @conference {cRuiz-Hidalgo09, title = {Comparison of MPEG-7 descriptors for long term selection of reference frames}, booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009}, year = {2009}, pages = {941{\textendash}944}, address = {Taipei, Taiwan}, isbn = {0-8194-2103-0}, doi = {10.1109/ICASSP.2009.4959740}, url = {http://hdl.handle.net/2117/8816}, author = {Ruiz-Hidalgo, J. and Salembier, P.} } @article {aSalembier09, title = {Connected operators: A review of region-based morphological image processing techniques}, journal = {IEEE Signal Processing Magazine}, volume = {6}, year = {2009}, pages = {136{\textendash}157}, issn = {1053-5888}, doi = {10.1109/MSP.2009.934154}, author = {Salembier, P. and Wilkinson, M.H.F.} } @conference {cDimiccoli09, title = {Exploiting T-junctions for depth segregation in single images}, booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009}, year = {2009}, address = {Taipei, Taiwan}, author = {Dimiccoli, M. and Salembier, P.} } @conference {cRolon09a, title = {Generalized lifting with adaptive local pdf estimation for image coding}, booktitle = {Picture coding symposium, PCS 2009}, year = {2009}, address = {Chicago, USA}, author = {Rol{\'o}n, J. and Mendon{\c c}a, E. and Salembier, P.} } @conference {cDimiccoli09a, title = {Hierarchical region-based representation for segmentation and filtering with depth in single images}, booktitle = {IEEE International Conference on Image Processing, ICIP 2009}, year = {2009}, address = {Cairo, Egypt}, author = {Dimiccoli, M. and Salembier, P.} } @conference {cButko09, title = {Improving Detection of Acoustic Events Using Audiovisual Data and Feature Level Fusion}, booktitle = {10th Annual Conference of the International Speech Communication Association}, year = {2009}, pages = {1147{\textendash}1150}, isbn = {978-1-61567-692-7}, url = {http://gps-tsc.upc.es/imatge/_Xgiro/research/publications/2009/interspeech.pdf}, author = {Butko, T. and Cristian Canton-Ferrer and Segura, C. and Xavier Gir{\'o}-i-Nieto and Nadeu, C. and Hernando, J. and Casas, J.} } @conference {cSanchez-Riera09, title = {Indoor PTZ camera calibration with concurrent PT axes}, booktitle = {Fourth International Conference on Computer Vision Theory and Applications}, year = {2009}, pages = {45{\textendash}50}, abstract = {

The introduction of active (pan-tilt-zoom or PTZ) cameras in Smart Rooms in addition to fixed static cameras allows to improve resolution in volumetric reconstruction, adding the capability to track smaller objects with higher precision in actual 3D world coordinates. To accomplish this goal, precise camera calibration data should be available for any pan, tilt, and zoom settings of each PTZ camera. The PTZ calibration method proposed in this paper introduces a novel solution to the problem of computing extrinsic and intrinsic parameters for active cameras. We first determine the rotation center of the camera expressed under an arbitrary world coordinate origin. Then, we obtain an equation relating any rotation of the camera with the movement of the principal point to define extrinsic parameters for any value of pan and tilt. Once this position is determined, we compute how intrinsic parameters change as a function of zoom. We validate our method by evaluating the re-projection error and its stability for points inside and outside the calibration set.

}, isbn = {0-8186-7310-9}, doi = {10.5220/0001754900100015}, url = {http://visapp.visigrapp.org/Abstracts/2009/VISAPP_2009_Abstracts.htm}, author = {Sanchez-Riera, J. and Salvador, J. and Casas, J.} } @conference {cCabrera09, title = {LAVICAD: LAboratori VIrtual de Comunicacions Anal{\`o}giques i Digitals}, booktitle = {Jornada d{\textquoteright}Innovaci{\'o} Docent - RIMA (JID-RIMA)}, year = {2009}, month = {02/2009}, publisher = {UPCommons}, organization = {UPCommons}, address = {Barcelona, Catalonia}, abstract = {

Mitjan{\c c}ant el present ajut s{\textquoteright}ha ampliat l{\textquoteright}aplicaci{\'o} en xarxa LAVICAD (LAboratori VIrtual de COmunicacions Anal{\`o}giques i Digitals) que s{\textquoteright}ofereix de forma integrada dins de la plataforma d{\textquoteright}e-learning COM@WEB. LAVICAD {\'e}s una eina programada en Java i Matlab i est{\`a} formada per un conjunt de simuladors de la capa f{\'\i}sica de sistemes de comunicacions. Tots els simuladors es presenten en xarxa i es poden utilitzar pels estudiants des de qualsevol ordinador sense necessitat d{\textquoteright}instal{\textperiodcentered}laci{\'o} de cap tipus de software especial. Durant el curs 2007 2008 s{\textquoteright}han desenvolupat entre d{\textquoteright}altres dos l{\'\i}nies de treball. D{\textquoteright}una banda s{\textquoteright}ha programat l{\textquoteright}applet que emula la capa f{\'\i}sica de la televisi{\'o} digital terrestre, com a referent per a l{\textquoteright}ensenyament de sistemes de comunicacions avan{\c c}ats. D{\textquoteright}altra banda s{\textquoteright}ha treballat en la programaci{\'o} de noves funcionalitats de l{\textquoteright}eina LAVICAD, que permeten ajudar als professors en el seguiment i avaluaci{\'o} del treball continuat dels estudiants. En particular s{\textquoteright}ha programat la generaci{\'o} d{\textquoteright}una base de dades que cont{\'e} la informaci{\'o} dels usuaris que s{\textquoteright}han connectat i els resultats obtinguts a l{\textquoteright}executar un determinat simulador. Les dues l{\'\i}nies desenvolupades han de permetre durant l{\textquoteright}actual curs, consolidar l{\textquoteright}{\'u}s dels diferents simuladors per a la doc{\`e}ncia de les assignatures implicades al projecte.

}, url = {http://hdl.handle.net/2099/7235}, author = {Cabrera, M. and Xavier Gir{\'o}-i-Nieto and Rey, F. and Gasull, A. and Casas, J. and Villares, J. and Fernandez, J. and Sala {\'A}lvarez, josep and Espinosa Fricke, Pedro and Fern{\'a}ndez, Carlos Marcos and Cort{\'e}s, S. and Farr{\'e}, Miquel {\`A}ngel} } @inbook {bDimakis09, title = {The Memory Jog Service}, booktitle = {Computers in the Human Interaction Loop}, year = {2009}, pages = {207{\textendash}234}, publisher = {Springer}, organization = {Springer}, address = {London}, abstract = {

The CHIL Memory Jog service focuses on facilitating the collaboration of participants in meetings, lectures, presentations, and other human interactive events, occurring in indoor CHIL spaces. It exploits the whole set of the perceptual components that have been developed by the CHIL Consortium partners (e.g., person tracking, face identification, audio source localization, etc) along with a wide range of actuating devices such as projectors, displays, targeted audio devices, speakers, etc.

}, isbn = {978-1-84882-053-1}, doi = {10.1007/978-1-84882-054-8}, url = {http://www.springerlink.com/content/tg220751v5m1h356/}, author = {Dimakis, N. and Soldatos, J. and Polymenakos, L. and Sturm, J. and Neumann, J. and Casas, J.} } @conference {cRolon09, title = {Modeling of contours in wavelet domain for generalized lifting image compression}, booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009}, year = {2009}, address = {Taipei, Taiwan}, author = {Rol{\'o}n, J. and Ortega, A. and Salembier, P.} } @phdthesis {dDimiccoli09, title = {Monocular Depth Estimation for Image Segmentation and Filtering}, year = {2009}, school = {Universitat Polit{\`e}cnica de Catalunya (UPC)}, type = {phd}, author = {Dimiccoli, M.}, editor = {Salembier, P.} } @conference {cSuau09, title = {Multi-resolution illumination compensation for foreground extraction}, booktitle = {16th International Conference on Image Processing}, year = {2009}, pages = {3225{\textendash}3228}, abstract = {

Illumination changes may lead to false foreground (FG) segmentation and tracking results. Most of the existing FG extraction algorithms obtain a background (BG) estimation from temporal statistical parameters. Such algorithms consider a quasi-static BG which does not change but slowly. Therefore, fast illumination changes are not taken into account by the BG estimator and they are considered as FG. The aim of the proposed algorithm is to reduce illumination effects in video sequences in order to improve foreground segmentation performances.

}, doi = {http://dx.doi.org/10.1109/ICIP.2009.5414358}, url = {http://www.icip2009.org}, author = {Suau, X. and Casas, J. and Ruiz-Hidalgo, J.} } @inbook {bBernardin09, title = {Person Tracking}, booktitle = {Computers in the human interaction loop}, year = {2009}, pages = {11{\textendash}22}, publisher = {Springer}, organization = {Springer}, address = {London}, abstract = {

One of the most basic building blocks for the understanding of human actions and interactions is the accurate detection and tracking of persons in a scene. In constrained scenarios involving at most one subject, or in situations where persons can be confined to a controlled monitoring space or required to wear markers, sensors, or microphones, these tasks can be solved with relative ease. However, when accurate localization and tracking have to be performed in an unobtrusive or discreet fashion, using only distantly placed microphones and cameras, in a variety of natural and uncontrolled scenarios, the challenges posed are much greater. The problems faced by video analysis are those of poor or uneven illumination, low resolution, clutter or occlusion, unclean backgrounds, and multiple moving and uncooperative users that are not always easily distinguishable.

}, isbn = {978-1-84882-053-1}, doi = {10.1007/978-1-84882-054-8}, url = {http://www.springerlink.com/content/tj2x827107563616/}, author = {Bernardin, K. and Stiefelhagen, R. and Pnevmatikakis, A. and Lanz, O. and Brutti, A. and Casas, J. and Potamianos, G.} } @conference {cSalembier09, title = {Study on nonlocal morphological operators}, booktitle = {IEEE International Conference on Image Processing, ICIP 2009}, year = {2009}, address = {Cairo, Egypt}, author = {Salembier, P.} } @article {aCanton-Ferrer08, title = {Audiovisual head orientation estimation with particle filtering in multisensor scenarios}, journal = {EURASIP Journal on Advances in Signal Processing}, volume = {2008}, year = {2008}, month = {06/2007}, pages = {1{\textendash}13}, chapter = {276846}, abstract = {

This article presents a multimodal approach to head pose estimation of individuals in environments equipped with multiple cameras and microphones, such as SmartRooms or automatic video conferencing. Determining the individuals head orientation is the basis for many forms of more sophisticated interactions between humans and technical devices and can also be used for automatic sensor selection (camera, microphone) in communications or video surveillance systems. The use of particle filters as a unified framework for the estimation of the head orientation for both monomodal and multimodal cases is proposed. In video, we estimate head orientation from color information by exploiting spatial redundancy among cameras. Audio information is processed to estimate the direction of the voice produced by a speaker making use of the directivity characteristics of the head radiation pattern. Furthermore, two different particle filter multimodal information fusion schemes for combining the audio and video streams are analyzed in terms of accuracy and robustness. In the first one, fusion is performed at a decision level by combining each monomodal head pose estimation, while the second one uses a joint estimation system combining information at data level. Experimental results conducted over the CLEAR 2006 evaluation database are reported and the comparison of the proposed multimodal head pose estimation algorithms with the reference monomodal approaches proves the effectiveness of the proposed approach.

}, issn = {1687-6172}, doi = {10.1155/2008/276846}, url = {http://asp.eurasipjournals.com/content/2008/1/276846}, author = {Cristian Canton-Ferrer and Segura, C. and Casas, J. and M. Pard{\`a}s and Hernando, J.} } @article {aVilaplana08, title = {Binary partition trees for object detection}, journal = {IEEE transactions on image processing}, volume = {17}, number = {11}, year = {2008}, pages = {1{\textendash}16}, abstract = {

This paper discusses the use of binary partition trees (BPTs) for object detection. BPTs are hierarchical region-based representations of images. They define a reduced set of regions that covers the image support and that spans various levels of resolution. They are attractive for object detection as they tremendously reduce the search space. In this paper, several issues related to the use of BPT for object detection are studied. Concerning the tree construction, we analyze the compromise between computational complexity reduction and accuracy. This will lead us to define two parts in the BPT: one providing accuracy and one representing the search space for the object detection task. Then we analyze and objectively compare various similarity measures for the tree construction. We conclude that different similarity criteria should be used for the part providing accuracy in the BPT and for the part defining the search space and specific criteria are proposed for each case. Then we discuss the object detection strategy based on BPT. The notion of node extension is proposed and discussed. Finally, several object detection examples illustrating the generality of the approach and its efficiency are reported.

}, issn = {1057-7149}, doi = {10.1109/TIP.2008.2002841}, author = {Ver{\'o}nica Vilaplana and Marqu{\'e}s, F. and Salembier, P.} } @conference {cSalembier08, title = {Connected operators based on region-trees}, booktitle = {IEEE International Conference on Image Processing, ICIP 2008}, year = {2008}, address = {San Diego, USA}, author = {Salembier, P.} } @conference {cRolon08, title = {Image compression with generalized lifting and partial knowledge of the signal pdf}, booktitle = {IEEE International Conference on Image Processing, ICIP 2008}, year = {2008}, pages = {250{\textendash}254}, address = {San Diego, USA}, isbn = {88-86179-83-9}, author = {Rol{\'o}n, J. and Salembier, P. and Alameda, X.} } @conference {cDimiccoli08, title = {Monocular Depth by Nonlinear Diffusion}, booktitle = {IEEE Sixth Indian Conference on Computer Vision, Graphics \& Image Processing, ICVGIP 2008}, year = {2008}, pages = {140{\textendash}148}, address = {Bhubaneswar, India}, author = {Dimiccoli, M. and Morel, J. and Salembier, P.} } @article {aSalah08, title = {Multimodal identification and localization of users in a smart environment}, journal = {Journal on Multimodal user interfaces}, volume = {2}, number = {2}, year = {2008}, pages = {75{\textendash}91}, issn = {1783-7677}, doi = {10.1007/s12193-008-0008-y}, url = {http://hdl.handle.net/2117/6326}, author = {Salah, A. and Morros, J.R. and Luque, J. and Segura, C. and Hernando, J. and Ambekar, O. and Schouten, B. and Pauwels, E.} } @conference {cCanton-Ferrer08b, title = {Multimodal Real-Time Focus of Attention Estimation in SmartRooms}, booktitle = {CVPR 2008 Workshop on Human Communicative Behavior Analysis}, year = {2008}, pages = {1{\textendash}4}, isbn = {978-1-4244-2340}, author = {Cristian Canton-Ferrer and Segura, C. and M. Pard{\`a}s and Casas, J. and Hernando, J.} } @inbook {bCanton-Ferrer08b, title = {Multi-Person Tracking Strategies Based on Voxel Analysis}, booktitle = {Multimodal Technologies for Perception of Humans}, volume = {4625}, year = {2008}, pages = {91{\textendash}103}, publisher = {Springer}, organization = {Springer}, address = {Berlin / Heidelberg}, abstract = {

This paper presents two approaches to the problem of simultaneous tracking of several people in low resolution sequences from multiple calibrated cameras. Spatial redundancy is exploited to generate a discrete 3D binary representation of the foreground objects in the scene. Color information obtained from a zenithal camera view is added to this 3D information. The first tracking approach implements heuristic association rules between blobs labelled according to spatiotemporal connectivity criteria. Association rules are based on a cost function which considers their placement and color histogram. In the second approach, a particle filtering scheme adapted to the incoming 3D discrete data is proposed. A volume likelihood function and a discrete 3D re-sampling procedure are introduced to evaluate and drive particles. Multiple targets are tracked by means of multiple particle filters and interaction among them is modeled through a 3D blocking scheme. Evaluation over the CLEAR 2007 database yields quantitative results assessing the performance of the proposed algorithm for indoor scenarios.

}, isbn = {978-3-540-68584-5}, doi = {10.1007/978-3-540-68585-2_7}, url = {http://www.springerlink.com/content/k08w4000844220gr/}, author = {Cristian Canton-Ferrer and Salvador, J. and Casas, J. and M. Pard{\`a}s} } @conference {cHaro08, title = {On the non-uniform complexity of brain connectivity}, booktitle = {5th IEEE International Symposium on Biomedical Imaging (ISBI 2008)}, year = {2008}, month = {05/2008}, publisher = {IEEE}, organization = {IEEE}, address = {Paris}, abstract = {

A stratification and manifold learning approach for analyzing High Angular Resolution Diffusion Imaging (HARDI) data is introduced in this paper. HARDI data provides high- dimensional signals measuring the complex microstructure of biological tissues, such as the cerebral white matter. We show that these high-dimensional spaces may be understood as unions of manifolds of varying dimensions/complexity and densities. With such analysis, we use clustering to characterize the structural complexity of the white matter. We briefly present the underlying framework and numerical experiments illustrating this original and promising approach.

}, keywords = {biodiffusion, biological tissues, biology computing, brain, brain connectivity, cellular biophysics, cerebral white matter, Clustering methods, complex microstructure, density, Density measurement, Diffusion tensor imaging, Geometry, high-angular resolution diffusion imaging, high-dimensional spaces, High-resolution imaging, Image analysis, Image resolution, Magnetic resonance imaging, manifold learning approach, Microstructure, molecular biophysics, nonuniform complexity, Point processes, Poisson processes, Signal resolution, stratification learning, Switches, Tensile stress, Unsupervised learning}, doi = {10.1109/ISBI.2008.4541139}, author = {Haro, G. and Lenglet, C. and Sapiro, Guillermo and Thompson, P.} } @inbook {bSalembier08, title = {Operateur connexe et arbre des coupes}, booktitle = {Morphologie math{\'e}matique 1: approches deterministes}, year = {2008}, pages = {151{\textendash}172}, publisher = {Hermes, Lavoisier}, organization = {Hermes, Lavoisier}, edition = {L. Najman and H. Talbot (Eds.)}, isbn = {978-2-7462-1841-3}, author = {Salembier, P.} } @conference {cCanton-Ferrer08a, title = {Particle Filtering and Sparse Sampling for Multi-Person 3D Tracking}, booktitle = {IEEE International Conference on Image Processing}, year = {2008}, pages = {2644{\textendash}2647}, isbn = {1-4244-1764-3}, doi = {10.1109/ICIP.2008.4712337}, author = {Cristian Canton-Ferrer and Sblendido, R. and Casas, J. and M. Pard{\`a}s} } @conference {cSalvador08, title = {Shape from Probability Maps with Image-Adapted Voxelization}, booktitle = {ECCV Workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications (M2SFA2)}, year = {2008}, pages = {1{\textendash}12}, isbn = {0-7803-9076-8}, author = {Salvador, J. and Casas, J.} } @article {aCraene08, title = {Unbiased group-wise alignment by iterative central tendency estimations}, journal = {Mathematical modeling of natural phenomena}, volume = {3}, number = {6}, year = {2008}, pages = {2{\textendash}32}, issn = {0973-5348}, url = {http://hdl.handle.net/2117/8140}, author = {de Craene, M. and Macq, B. and Marqu{\'e}s, F. and Salembier, P. and Warfield, S.} } @article {aMostefa07, title = {The CHIL Audiovisual Corpus for Lecture and Meeting Analysis inside Smart Rooms}, journal = {Language resources and evaluation}, volume = {41}, number = {3}, year = {2007}, month = {01/2008}, pages = {389{\textendash}407}, abstract = {

The analysis of lectures and meetings inside smart rooms has recently attracted much interest in the literature, being the focus of international projects and technology evaluations. A key enabler for progress in this area is the availability of appropriate multimodal and multi-sensory corpora, annotated with rich human activity information during lectures and meetings. This paper is devoted to exactly such a corpus, developed in the framework of the European project CHIL, {\textquotedblleft}Computers in the Human Interaction Loop{\textquotedblright}. The resulting data set has the potential to drastically advance the state-of-the-art, by providing numerous synchronized audio and video streams of real lectures and meetings, captured in multiple recording sites over the past 4 years. It particularly overcomes typical shortcomings of other existing databases that may contain limited sensory or monomodal data, exhibit constrained human behavior and interaction patterns, or lack data variability. The CHIL corpus is accompanied by rich manual annotations of both its audio and visual modalities. These provide a detailed multi-channel verbatim orthographic transcription that includes speaker turns and identities, acoustic condition information, and named entities, as well as video labels in multiple camera views that provide multi-person 3D head and 2D facial feature location information. Over the past 3 years, the corpus has been crucial to the evaluation of a multitude of audiovisual perception technologies for human activity analysis in lecture and meeting scenarios, demonstrating its utility during internal evaluations of the CHIL consortium, as well as at the recent international CLEAR and Rich Transcription evaluations. The CHIL corpus is publicly available to the research community

}, issn = {1574-020X}, doi = {10.1007/s10579-007-9054-4}, author = {Mostefa, D. and Moreau, N. and Choukri, K. and Potamianos, G. and Chu, S. and Tyagi, A. and Casas, J. and Turmo, J. and Cristoforetti, L. and Tobia, F. and Pnevmatikakis, A. and Mylonakis, V. and Talantzis, F. and Burger, S. and Stiefelhagen, R. and Bernardin, K. and Rochet, C.} } @conference {cMorros07, title = {Event recognition for meaningful Human-Computer interaction in smart environments}, booktitle = {Proceedings of the eNTERFACE{\textquoteright}07 Workshop on Multimodal Interfaces}, year = {2007}, month = {08/2007}, abstract = {

The aim of this project is to monitor a room for the purposes of analysing the interactions and identities of a small set of individ- uals. We work with multiple uncalibrated sensors that observe a single environment and generate multimodal data streams. These streams are processed with the help of a generic client-server middleware called SmartFlow. Modules for visual motion de- tection, visual face tracking, visual face identification, visual op- portunistic sensing, audio-based localization, and audio-based identification are implemented and integrated under SmartFlow to work in coordination across different platforms.

}, keywords = {Audio systems, Image motion analysis, Image sensors, pattern recognition}, isbn = { 978-2874631054}, author = {Morros, J.R. and Albert Ali Salah and Ben Schouten and Carlos Segura Perales and Jordi Luque Serrano and Onkar Ambekar and Ceren Kayalar and Cem Keskin and Lale Akarun} } @conference {cPetras07, title = {Flexible test-bed for unusual behavior detection}, booktitle = {6th ACM International Conference on Image and Video Retrieval}, year = {2007}, pages = {105{\textendash}108}, isbn = {0 646 34170 7}, author = {Petras, I. and Beleznai, C. and Dedeoglu, Y. and M. Pard{\`a}s and Kov{\'a}cs, L. and Szl{\'a}vik, Z. and Havasi, L. and Szir{\'a}nyi, T. and T{\"o}reyin, B. and G{\"u}d{\"u}kbay, U. and Cetin, E. and Cristian Canton-Ferrer} } @conference {cRolon07, title = {Generalized Lifting For Sparse Image Representation and Coding}, booktitle = {Picture Coding Symposium, PCS 2007}, year = {2007}, pages = {234{\textendash}238}, address = {Lisbon, Portugal}, isbn = {88-86179-83-9}, author = {Rol{\'o}n, J. and Salembier, P.} } @article {aSole07a, title = {Generalized lifting prediction optimization applied to lossless image compression}, journal = {IEEE signal processing letters}, volume = {14}, number = {10}, year = {2007}, pages = {695{\textendash}698}, issn = {1070-9908}, author = {Sol{\'e}, J. and Salembier, P.} } @conference {cDimiccoli07a, title = {Geometrical Filtering Scheme with Connected Operators and Image Inpainting}, booktitle = {SPIE Visual Communcations and Image Processing 2007}, year = {2007}, pages = {1{\textendash}14}, address = {San Jose, CA, USA}, author = {Dimiccoli, M. and Salembier, P.} } @conference {cRuiz-Hidalgo07, title = {Long term selection of reference frame sub-blocks using MPEG-7 indexing metadata}, booktitle = {International Conference on Acoustics, Speech and Signal Processing, ICASSP 2007}, year = {2007}, month = {04/2007}, pages = {669{\textendash}672}, address = {Honolulu, Hawaii}, author = {Ruiz-Hidalgo, J. and Salembier, P.} } @conference {cSegura07, title = {Multimodal Head Orientation towards Attention Tracking in Smart Rooms}, booktitle = {2007 International Conference on Acoustics, Speech and Signal Processing}, year = {2007}, abstract = {

This paper presents a multimodal approach to head pose estimation and 3D gaze orientation of individuals in a SmartRoom environment equipped with multiple cameras and microphones. We first introduce the two monomodal approaches as reference. In video, we estimate head orientation from color information by exploiting spatial redundancy among cameras. Audio information is processed to estimate the direction of the voice produced by a speaker making use of the directivity characteristics of the head radiation pattern. Two multimodal information fusion schemes working at data and decision levels are analyzed in terms of accuracy and robustness of the estimation. Experimental results conducted over the CLEAR evaluation database are reported and the comparison of the proposed multimodal head pose estimation algorithms with the reference monomodal approaches proves the effectiveness of the proposed approach.

}, author = {Segura, C. and Abad, A. and Casas, J. and Hernando, J.} } @conference {cCanton-Ferrer07, title = {Multi-Person Tracking Strategies Based on Voxel Analysis}, booktitle = {CLEAR{\textquoteright}07 Second International Evaluation Workshop on Classification of Events, Activities and Relationships}, year = {2007}, pages = {1{\textendash}12}, isbn = {978-3-540-68584-5}, author = {Cristian Canton-Ferrer and Salvador, J. and Casas, J. and M. Pard{\`a}s} } @conference {cDimiccoli07, title = {Perceptual filtering with connected operators and image inpainting}, booktitle = {Proc. of International Symposium on Mathematical Morphology, ISMM 2007}, year = {2007}, pages = {227{\textendash}238}, address = {Rio de Janeiro, Brazil}, isbn = {978-85-17-00032-4}, author = {Dimiccoli, M. and Salembier, P.} } @article {aSole07, title = {Quadratic Interpolation and Linear Lifting Design}, journal = {Eurasip Journal on Applied Signal Processing}, volume = {1}, number = {1}, year = {2007}, pages = {1{\textendash}9}, issn = {1110-8657}, author = {Sol{\'e}, J. and Salembier, P.} } @conference {cHaro07, title = {Stratification Learning: Detecting Mixed Density and Dimensionality in High Dimensional Point Clouds}, booktitle = {Neural Information Processing Systems NIPS}, year = {2007}, month = {12/2007}, publisher = {NIPS}, organization = {NIPS}, address = {Montreal}, abstract = {

The study of point cloud data sampled from a stratification, a collection of manifolds with possible different dimensions, is pursued in this paper. We present a technique for simultaneously soft clustering and estimating the mixed dimensionality and density of such structures. The framework is based on a maximum likelihood estimation of a Poisson mixture model. The presentation of the approach is completed with artificial and real examples demonstrating the importance of extending manifold learning to stratification learning.

}, author = {Haro, G. and Randall, Gregory and Sapiro, Guillermo} } @article {aSalembier07, title = {Structure description tools}, journal = {Journal of the American Society for Information Science}, volume = {58}, number = {9}, year = {2007}, pages = {1329{\textendash}1337}, issn = {0002-8231}, author = {Salembier, P. and Benitez, A.B} } @inbook {bAbad07, title = {UPC Audio, Video and Multimodal Person Tracking Systems in the CLEAR Evaluation Campaign}, booktitle = {Lecture notes in computer science}, volume = {4122}, year = {2007}, pages = {93{\textendash}104}, publisher = {Springer}, organization = {Springer}, address = {Berlin / Heidelberg}, abstract = {

Reliable measures of person positions are needed for computational perception of human activities taking place in a smart-room environment. In this work, we present the Person Tracking systems developed at UPC for audio, video and audio-video modalities in the context of the EU funded CHIL project research activities. The aim of the designed systems, and particularly of the new contributions proposed, is to deal robustly in both single and multiperson localization tasks independently on the environmental conditions. Besides the technology description, experimental results conducted for the CLEAR evaluation workshop are also reported.

}, isbn = {978-3-540-69567-7}, doi = {10.1007/978-3-540-69568-4_6}, author = {Abad, A. and Cristian Canton-Ferrer and Segura, C. and Landabaso, J. and Macho, D. and Casas, J. and Hernando, J. and M. Pard{\`a}s and Nadeu, C.} } @conference {cCanton-Ferrer06, title = {3D Human Action Recognition In Multiple View Scenarios}, booktitle = {2ones Jornades UPC de Investigaci{\'o}n en Autom{\'a}tica, Visi{\'o}n y Rob{\'o}tica}, year = {2006}, pages = {1{\textendash}5}, isbn = {84-7653-885-5}, author = {Cristian Canton-Ferrer and Cristian Canton-Ferrer and Casas, J. and M. Pard{\`a}s and Sargin, M. and Tekalp, M.} } @conference {cSole06a, title = {Adaptive Quadratic Interpolation Methods for Lifting Steps Construction}, booktitle = {IEEE International Symposium on Signal Processing and Information Technology, , ISSPIT 2006}, year = {2006}, pages = {1{\textendash}8}, address = {Vancouver, Canada}, isbn = {1-4244-1437-7}, author = {Sol{\'e}, J. and Salembier, P.} } @conference {cSole06, title = {A Common Formulation for Interpolation, Prediction, and Update Lifting Design,}, booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2006}, year = {2006}, pages = {1{\textendash}4}, address = {Toulouse, France}, isbn = {978-83-921340-2-2}, author = {Sol{\'e}, J. and Salembier, P.} } @conference {cSalvador06, title = {Image-adapted voxelization in multicamera settings}, booktitle = {International Workshop on Multimedia Signal Processing}, year = {2006}, pages = {161{\textendash}165}, abstract = {

This paper presents a new procedure to explore 3D for visual analysis in multicamera environments. We propose a 3D geometry to sample (voxelize) the space when checking the consistency of the analyzed features in the multiple views. Contrary to regular voxelization, the proposed geometry is irregular in 3D, but becomes regular once projected onto camera images. The aim is to better exploit the redundancy and the enriched information provided in multiview frameworks at the analysis stage. This is accomplished by balancing the usage of the available data (i.e. captured pixels) across the multiple cameras, instead of focusing in a regular sampling of the 3D space from which we do not have direct data. An efficient recursive algorithm that uses the proposed geometry is outlined, and the experimental results reflect higher accuracy than regular voxelization with equivalent restrictions for the chosen multiview analysis applications

}, isbn = {0-7803-3258-X}, author = {Salvador, J. and Casas, J.} } @conference {cCasas06, title = {Image-based Multi-view Scene Analysis using {\textquoteright}Conexels{\textquoteright}}, booktitle = {HCSNet Workshop on the Use of Vision in Human-Computer Interaction (VisHCI 2006)}, year = {2006}, pages = {203{\textendash}212}, abstract = {

Multi-camera environments allow constructing volumetric models of the scene to improve the analysis performance of computer vision algorithms (e.g. disambiguating occlusion). When representing volumetric results of image-based multi-camera analysis, a direct approach is to scan the 3D space with regular voxels. Regular voxelization is good at high spatial resolutions for applications such as volume visualization and rendering of synthetic scenes generated by geometric models, or to represent data resulting from direct 3D data capture (e.g. MRI). However, regular voxelization shows a number of drawbacks for visual scene analysis, where direct measurements on 3D voxels are not usually available. In this case, voxel values are computed rather as a result of the analysis on ?projected? image data.

In this paper, we first provide some statistics to show how voxels project to ?unbalanced? sets of image data in common multi-view analysis settings. Then, we propose a 3D geometry for multi-view scene analysis providing a better balance in terms of the number of pixels used to analyse each elementary volumetric unit. The proposed geometry is non-regular in 3D space, but becomes regular once projected onto camera images, adapting the sampling to the images. The aim is to better exploit multiview image data by balancing its usage across multiple cameras instead of focusing in regular sampling of 3D space, from which we do not have direct measurements. An efficient recursive algorithm using the proposed geometry is outlined. Experimental results reflect better balance and higher accuracy for multi-view analysis than regular voxelization with equivalent restrictions.

}, keywords = {epipolar geometry, Multi-view analysis, volume voxelization}, isbn = {1-920-68238-4}, url = {http://crpit.com/Vol56.html}, author = {Casas, J. and Salvador, J.} } @phdthesis {dSole06, title = {Optimization and Generalization of Lifting Schemes: Application to Lossless Image Compression}, year = {2006}, school = {Universitat Polit{\`e}cnica de Catalunya (UPC)}, type = {phd}, abstract = {

This Ph.D. thesis dissertation addresses multi-resolution image decomposition, a key issue in signal processing that in recent years has contributed to the emergence of the JPEG2000 image compression standard. JPEG2000 incorporates many interesting features, mainly due to the discrete wavelet transform stage and to the EBCOT entropy coder. Wavelet analysis perform multi-resolution decompositions that decorrelate signal and separate information in useful frequency-bands, allowing flexible post-coding. In JPEG2000, decomposition is computed through the lifting scheme, the so-called second generation wavelets. This fact has focused the community interest on this tool. Many works have been recently proposed in which lifting is modified, improved, or included in a complete image coding algorithm. The Ph.D. thesis dissertation follows this research line. Lifting is analyzed, proposals are made within the scheme, and their possibilities are explored. Image compression is the main objective and it is principally assessed by means of coding transformed signal with EBCOT and SPIHT coders. Starting from this context, the work diverges in two distinct paths, the linear and the nonlinear one. The linear lifting filter construction is based on the idea of quadratic interpolation and the underlying linear restriction due to the wavelet transform coefficients. The result is a flexible framework that allows the creation of new transforms using different criteria and that may adapt to the image statistics. The nonlinear part is founded on the adaptive lifting scheme, which is extensively analyzed and as a consequence, a generalization of the lifting is proposed. The discrete version of the generalized lifting is developed leading to filters that achieve good compression results, specially for biomedical and remote sensing images

}, url = {http://hdl.handle.net/10803/6897}, author = {Sol{\'e}, J.} } @phdthesis {dRuiz-Hidalgo06, title = {On the Synergy between indexing and compression representations for video sequences}, year = {2006}, school = {Universitat Polit{\`e}cnica de Catalunya (UPC)}, type = {phd}, author = {Ruiz-Hidalgo, J.}, editor = {Salembier, P.} } @conference {cAbad06, title = {UPC Audio, Video and Multimodal Person Tracking Systems in the CLEAR Evaluation Campaign}, booktitle = {CLEAR{\textquoteright}06 Evaluation Campaign and Workshop - Classification of Events, Activities and Relationships}, year = {2006}, pages = {93{\textendash}104}, isbn = {978-3-540-69567-7}, author = {Abad, A. and Cristian Canton-Ferrer and Cristian Canton-Ferrer and Segura, C. and Landabaso, J. and Macho, D. and Casas, J. and Hernando, J. and M. Pard{\`a}s and Nadeu, C.} } @article {aRuiz-Hidalgo06, title = {On the use of indexing metadata to improve the efficiency of video compression}, journal = {IEEE transactions on circuits and systems for video technology}, volume = {16}, number = {3}, year = {2006}, pages = {410{\textendash}419}, abstract = {

For the last years, video indexing and video compression have been considered as two separate functionalities. However, multimedia content is growing in such a rate that multimedia services will need to consider both the compression and the indexing aspects of the content in order to efficiently manage this audio-visual content. Therefore, it is interesting to study the synergy between the representations of compression and indexing and in particular to find new schemas that allow the possibility to exploit indexing/compression information in order to increase the efficiency of video compression/indexing capabilities. The principal contribution of this paper is to study and develop new techniques where the compression efficiency of video codecs can be improved by the use of indexing metadata where indexing metadata refers to information that has been generated to support indexing capabilities.

}, keywords = {H.264, Indexing Metadata, MPEG-7, Video Coding}, issn = {1051-8215}, author = {Ruiz-Hidalgo, J. and Salembier, P.} } @conference {cSalvador06a, title = {Voxelitzaci{\'o} Adaptada a les Imatges en Entorns Multic{\`a}mera}, booktitle = {2ones Jornades UPC de Investigaci{\'o}n en Autom{\'a}tica, Visi{\'o}n y Rob{\'o}tica}, year = {2006}, pages = {1{\textendash}6}, isbn = {978-3-540-26042-4}, author = {Salvador, J. and Casas, J.} } @conference {cSole05, title = {Adaptive Generalized Prediction for Lifting Schemes}, booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2005}, year = {2005}, pages = {205{\textendash}208}, address = {Philadelphia, USA}, isbn = {1-4244-1011-8}, author = {Sol{\'e}, J. and Salembier, P.} } @inbook {bGiro-i-Nieto05, title = {Automatic extraction and analysis of visual objects information}, booktitle = {Multimedia content and the semantic web}, year = {2005}, pages = {203{\textendash}221}, publisher = {Wiley}, organization = {Wiley}, chapter = {7}, isbn = {978-0-470-85753-3}, doi = {10.1002/0470012617.ch7}, url = {http://eu.wiley.com/WileyCDA/WileyTitle/productCd-0470857536.html}, author = {Xavier Gir{\'o}-i-Nieto and Ver{\'o}nica Vilaplana and Marqu{\'e}s, F. and Salembier, P.} } @conference {cAnton05, title = {Collaborative Network Space: Infrastructure and Learning Application}, booktitle = {IEEE Region 8 EUROCON 2005 Conference: Computer as a tool.}, year = {2005}, pages = {803{\textendash}806}, isbn = {1-4244-0050-3}, url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=01630054}, author = {Anton, M. and Vall-Llosera, M. and Jordi Torres and Romeu, J. and Jofre, L. and Sole, F. and Marqu{\'e}s, F. and Sabate, F. and Berenguer, J.} } @conference {cSayrol05, title = {Development of a platform offering video copyright protection and security against illegal distribution}, booktitle = {Security, Steganography, and Watermarking of Multimedia Contents}, year = {2005}, pages = {76{\textendash}83}, isbn = {9963-607-06-3}, author = {Elisa Sayrol and Soriano, M. and Fernandez, M. and Casanelles, J. and Tom{\`a}s, J.} } @conference {cMarques05, title = {El concepto NetCampus}, booktitle = {3es Jornadas de la C{\'a}tedra Telef{\'o}nica-UPC}, year = {2005}, pages = {15{\textendash}20}, url = {https://catedratelefonica.upc.edu/documents/llibres/docs/el_espacio_innovador_y_la_red.pdf}, author = {Marqu{\'e}s, F. and Jofre, L. and Sole, F. and Sabate, F. and Berenguer, J. and Romeu, J. and Jordi Torres} } @book {eJofre05, title = {El "Espacio Innovador" y la red}, year = {2005}, url = {http://www.upc.edu/web/CatedraTelefonicaUPC}, author = {Jofre, L. and Sole, F. and Sabate, F. and Berenguer, J. and Marqu{\'e}s, F. and Romeu, J. and Jordi Torres} } @conference {cSoriano05, title = {Multimedia copyright protection platform demonstrator}, booktitle = {Third International Conference on Trust Management (iTrust{\textquoteright}05)}, year = {2005}, pages = {411{\textendash}414}, doi = {10.1007/11429760_32}, url = {http://dx.doi.org/10.1007/11429760_32}, author = {Soriano, M. and Fernandez, M. and Elisa Sayrol and Buliart, J. and Casanelles, J. and Pegueroles, J. and Juan Hern{\'a}ndez Serrano} } @inbook {bSoriano05, title = {Multimedia Copyright Protection Platform Demonstrator}, booktitle = {Lecture notes in computer science}, volume = {3477}, year = {2005}, pages = {76{\textendash}83}, issn = {0302-9743}, url = {http://www.springerlink.com/(n0yw1g55rs45pg55g5zcinrm)/app/home/contribution.asp?referrer=parent\&backto=issue,32,34;journal,197,2212;linkingpublicationresults,1:105633,1}, author = {Soriano, M. and Fernandez, M. and Elisa Sayrol and Tom{\`a}s, J. and Casanelles, J. and Pegueroles, J. and Juan Hern{\'a}ndez Serrano} } @conference {cVilaplana05, title = {Region-based extraction and analysis of visual objects information}, booktitle = {Fourth International Workshop on Content-Based Multimedia Indexing, CBMI 2005}, year = {2005}, address = {Riga, Letonia}, abstract = {

In this paper, we propose a strategy to detect objects from\ still images that relies on combining two types of models: a\ perceptual and a structural model. The algorithms that are\ proposed for both types of models make use of a regionbased description of the image relying on a Binary Partition\ Tree. Perceptual models link the low-level signal description with semantic classes of limited variability. Structural\ models represent the common structure of all instances by\ decomposing the semantic object into simpler objects and\ by defining the relations between them using a DescriptionGraph.

}, isbn = {0-7803-6293-4}, author = {Ver{\'o}nica Vilaplana and Xavier Gir{\'o}-i-Nieto and Salembier, P. and Marqu{\'e}s, F.} } @conference {cSole04, title = {Adaptive Discrete Generalized Lifting for Lossless Compression}, booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2004}, year = {2004}, pages = {1{\textendash}5}, address = {Montreal, Canada}, isbn = {1-4244-1764-3}, author = {Sol{\'e}, J. and Salembier, P.} } @book {eJofre04, title = {El {\textquoteright}Profesional Innovador{\textquoteright} y la red}, year = {2004}, url = {http://catedratelefonica.upc.edu/documents/llibres/docs/jornada_2004_catedra_telf_upc.pdf}, author = {Jofre, L. and Sole, F. and Sabate, F. and Marqu{\'e}s, F. and Romeu, J. and Jordi Torres} } @conference {cSalerno04, title = {Object recognition based on Binary Partition Trees}, booktitle = {IEEE International Conference on Image Processing}, year = {2004}, pages = {929{\textendash}932}, author = {Salerno, O. and M. Pard{\`a}s and Ver{\'o}nica Vilaplana and Marqu{\'e}s, F.} } @conference {cSole04a, title = {Prediction design for discrete generalized lifting}, booktitle = {Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2004}, year = {2004}, pages = {78{\textendash}82}, address = {Brussels, Belgium}, isbn = {978-1-4244-3610-1}, author = {Sol{\'e}, J. and Salembier, P.} } @conference {cJofre04, title = {Una Enginyeria per a la Societat del Coneixement}, booktitle = {II Congr{\'e}s d{\textquoteright}Enginyeria en Llengua Catalana}, year = {2004}, url = {http://www.eicc.cat/celc/formacio.htm}, author = {Jofre, L. and Sole, F. and Sabate, F. and Marqu{\'e}s, F. and Romeu, J. and Jordi Torres} } @conference {cCasas03, title = {Advanced content-based semantic scene analysis and information retrieval: the Schema Project}, booktitle = {4th European Workshop on Image Analysis for Multimedia Interactive Services_x000D_}, year = {2003}, pages = {43{\textendash}45}, abstract = {

The aim of the SCHEMA Network of Excellence is to bring together a critical mass of universities, research centers, industrial partners and end users, in order to design a reference system for content-based semantic scene analysis, interpretation and understanding. Relevant research areas include: contentbased multimedia analysis and automatic annotation of semantic multimedia content, combined textual and multimedia information retrieval, semantic-web, MPEG-7 and MPEG-21 standards, user interfaces and human factors. In this paper, recent advances in content-based analysis, indexing and retrieval of digital media within the SCHEMA Network are presented. These advances will
be integrated in the SCHEMA module-based, expandable reference system.

}, author = {Izquierdo, E. and Casas, J. and Leonardi, R. and Migliorati, P. and O{\textquoteright}Connor, N. and Kompatsiaris, I. and Strintzis, M.} } @phdthesis {dLlach03, title = {Analysis of Video Sequences for Content Description. Table of Contents \& Index Creation and Scene Classification}, year = {2003}, school = {Universitat Polit{\`e}cnica de Catalunya (UPC)}, type = {phd}, author = {Llach, J.}, editor = {Salembier, P.} } @conference {cRuiz-Hidalgo03, title = {Metadata-based coding tools for hybrid video codecs}, booktitle = {Picture Coding Symposium, PCS 2003}, year = {2003}, month = {04/2003}, pages = {473{\textendash}477}, address = {Saint-Malo, France}, author = {Ruiz-Hidalgo, J. and Salembier, P.} } @conference {cVentosa03, title = {Perceptual mask estimation from watermarked images}, booktitle = {SPIE Electronic Imaging 2003}, year = {2003}, pages = {10{\textendash}17}, isbn = {?}, author = {Ventosa, S. and Elisa Sayrol and Vidal, J.} } @conference {cO{\textquoteright}Connor03, title = {Region and object segmentation algorithms in the Qimera segmentation platform}, booktitle = {Third International Workshop on Content-Based Multimedia Indexing}, year = {2003}, pages = {95{\textendash}103}, abstract = {

In this paper we present the Qimera segmentation platform and describe the different approaches to segmentation that have been implemented in the system to date. Analysis techniques have been implemented for both region-based and object-based segmentation. The region-based segmentation algorithms include: a colour segmentation algorithm based on a modified Recursive Shortest Spanning Tree (RSST) approach, an implementation of a colour image segmentation algorithm based on the K-Means-with-Connectivity-Constraint (KMCC) algorithm and an approach based on the Expectation Maximization (EM) algorithm applied in a 6D colour/texture space. A semi-automatic approach to object segmentation that uses the modified RSST approach is outlined. An automatic object segmentation approach via snake propagation within a level-set framework is also described. Illustrative segmentation results are presented in all cases. Plans for future research within the Qimera project are also discussed.

}, isbn = {978-84-612-2373-2}, author = {O{\textquoteright}Connor, N. and Sav, S. and Adamek, T. and Mezaris, V. and Kompatsiaris, I. and Lui, T. and Izquierdo, E. and Ferran, C. and Casas, J.} } @article {aComas03, title = {Unbalanced multiple description video coding based on a rate-distortion optimization}, journal = {Eurasip Journal on Applied Signal Processing}, volume = {2003}, number = {1}, year = {2003}, pages = {81{\textendash}90}, issn = {1110-8657}, author = {Comas, D. and Singh, R. and Ortega, A. and Marqu{\'e}s, F.} } @article {aAvrithis03, title = {Unified Access to Heterogeneous Audiovisual Archives}, journal = {Journal of universal computer science}, volume = {9}, number = {6}, year = {2003}, pages = {510{\textendash}519}, abstract = {

In this paper, an integrated information system is presented that offers enhanced search and retrieval capabilities to users of heterogeneous digital audiovisual (a/v) archives. This innovative system exploits the advances in handlings a/v content and related metadata, as introduced by MPEG-4 and worked out by MPEG-7, to offer advanced services characterized by the tri-fold semantic phrasing of the request (query), unified handling and personalized response. The proposed system is targeting the intelligent extraction of semantic information from a/v and text related data taking into account the nature of the queries that users my issue, and the context determined by user profiles. It also provides a personalization process of the response in order to provide end_users with desired information. From a technical point of view, the FAETHON system plays the role of an intermediate access server residing between the end users and multiple heterogeneous audiovisual archives organized according to the new MPEG standards.

}, issn = {0948-6968}, doi = {10.3217/jucs-009-06-0510}, url = {http://www.jucs.org/jucs_9_6}, author = {Avrithis, Y. and Stamou, G. and Wallace, M. and Marqu{\'e}s, F. and Salembier, P. and Xavier Gir{\'o}-i-Nieto and Haas, W. and Vallant, H. and Zufferey, M.} } @conference {cAvrithis03, title = {Unified access to heterogeneous audiovisual archives}, booktitle = {International Conference on Knowledge Management}, year = {2003}, pages = {1{\textendash}2}, address = {Graz, Austria}, author = {Avrithis, Y. and Stamou, G. and Wallace, M. and Marqu{\'e}s, F. and Salembier, P. and Xavier Gir{\'o}-i-Nieto and Haas, W. and Vallant, H. and Zufferey, M.} } @article {aSchelkens03, title = {Wavelet coding of volumetric medical datasets}, journal = {Medical Imaging, IEEE Transactions on}, volume = {22}, year = {2003}, month = {march}, pages = {441 -458}, abstract = {

Several techniques based on the three-dimensional (3-D) discrete cosine transform (DCT) have been proposed for volumetric data coding. These techniques fail to provide lossless coding coupled with quality and resolution scalability, which is a significant drawback for medical applications. This paper gives an overview of several state-of-the-art 3-D wavelet coders that do meet these requirements and proposes new compression methods exploiting the quadtree and block-based coding concepts, layered zero-coding principles, and context-based arithmetic coding. Additionally, a new 3-D DCT-based coding scheme is designed and used for benchmarking. The proposed wavelet-based coding algorithms produce embedded data streams that can be decoded up to the lossless level and support the desired set of functionality constraints. Moreover, objective and subjective quality evaluation on various medical volumetric datasets shows that the proposed algorithms provide competitive lossy and lossless compression results when compared with the state-of-the-art.

}, keywords = {Algorithms, Computer-Assisted, Data Compression, discrete cosine transforms, embedded coding, embedded data streams, functionality constraints, image coding, Image Enhancement, Image Interpretation, Imaging, JPEG2000, layered zero coding, lossless compression, medical diagnostic imaging, medical image compression, medical image processing, Numerical Analysis, objective quality evaluation, progressive image transmission, quadtree coding, reviews, Signal Processing, subjective quality evaluation, Three-Dimensional, volumetric coding, wavelet transforms}, issn = {0278-0062}, doi = {10.1109/TMI.2003.809582}, author = {Schelkens, P. and Munteanu, A. and Barbarien, J. and Galca, M. and Xavier Gir{\'o}-i-Nieto and Cornelis, J.} } @conference {cVidal02, title = {Color Image Watermarking Using Channel-State Knowledge}, booktitle = {SPIE Electronic Imaging 2002}, year = {2002}, pages = {214{\textendash}221}, isbn = {0-8194-4415-4}, author = {Vidal, J. and Maribel, M. and Elisa Sayrol} } @conference {cSalembier02a, title = {Connected Operators Based on Reconstruction Process for Size and Motion Simplification}, booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2002}, year = {2002}, month = {05/2002}, address = {Orlando, USA}, author = {Salembier, P. and Ruiz-Hidalgo, J.} } @inbook {bSalembier02b, title = {Description of a Single Multimedia Document}, booktitle = {Introduction to the mpeg-7: multimedia content description interface}, year = {2002}, pages = {111{\textendash}138}, publisher = {Wiley}, organization = {Wiley}, edition = {B. S. Manjunath, P. Salembier, T. Sikora (Eds.)}, chapter = {8}, isbn = {0471486787}, author = {Benitez, A.B and Martinez, J.M and Rising, H and Salembier, P.} } @conference {cMarques02a, title = {Facial Feature Segmentation from Frontal View Images}, booktitle = {11th European Signal Processing Conference (EUSIPCO 2002)}, year = {2002}, pages = {33{\textendash}36}, author = {Marqu{\'e}s, F. and Sobrevals, C.} } @conference {cSalembier02, title = {On Filters by Reconstruction for Size and Motion Simplification,}, booktitle = {Int. Symposium on Mathematical Morphology, ISMM 2002}, year = {2002}, month = {04/2002}, pages = {425{\textendash}434}, address = {Sydney, Australia}, author = {Salembier, P. and Ruiz-Hidalgo, J.} } @conference {cGarrido02, title = {A framework for the retrieval of multiple regions using Binary Partition Trees and low level descriptors}, booktitle = {11th European Signal Processing Conference, EUSIPCO 2002}, year = {2002}, pages = {512{\textendash}516}, address = {Toulouse, France}, author = {Garrido, L. and Salembier, P.} } @conference {cVallverdu02, title = {Graphical study of signals and systems}, booktitle = {14th annual World Conference on Educational Multimedia, Hypermedia \& Telecommunications}, year = {2002}, isbn = {0-8186-7919-0}, author = {Vallverdu, F. and Elisa Sayrol and Gasull, A. and Salavedra, J. and Moreno, A.} } @phdthesis {dGarrido02, title = {Hierarchical Region Based Processing of Images and Video Sequences: Application to Filtering, Segmentation and Information Retrieval}, year = {2002}, school = {Universitat Polit{\`e}cnica de Catalunya (UPC)}, type = {phd}, abstract = {

This work discusses the usefulness of hierarchical region based representations for image and video processing. Region based representations offer a way to perform a first level of abstraction and reduce the number of elements to process with respect to the classical pixel based representation. In this work the two representations that have demonstrated to be useful for region based processing are reviewed, namely region adjacency graphs and trees, and it is discussed why tree based representations are better suited for our purpose. In fact, trees allow representing the image in a hierarchical way and efficient and complex processing techniques can be applied on it. Two major issues are discussed in this work: how the hierarchical representation may be created from a given image and how the tree may be manipulated or processed. Two tree based representations have been developed: the Max-Tree, and the Binary Partition Tree. The Max-Tree structures in a compact way the connected components that arise from all possible level sets from a gray-level image. It is suitable for the implementation of anti-extensive connected operators, ranging from classical ones (for instance, area filter) to new ones (such as the motion filter developed in this work). The Binary Partition Tree structures the set of regions that are obtained during the execution of a region merging algorithm. Developed to overcome some of the drawbacks imposed by the Max-Tree {\textendash} in particular the lack of flexibility of the tree creation and the self-duality of the tree representation {\textendash}, it has demonstrated to be a representation useful for a rather large range of applications, as it is shown in this work. Processing strategies are focused on pruning techniques. Pruning techniques remove some of the branches of the tree based on an analysis algorithm applied on the nodes of the tree. Pruning techniques applied on the Max-Tree lead to anti-extensive operators, whereas self-dual operators are obtained on the Binary Partition Tree, if the tree is created in a self-dual manner. The pruning techniques that have been developed in this work are directed to the following applications: filtering, segmentation and content based image retrieval. The filtering (in the context of connected operators) and segmentation applications are based on the same principle: the nodes of the tree are analyzed according to a fixed criterion, and the decision to remove or preserve a node usually relies on a threshold applied on the former measured criterion. Pruning is then performed according to the previous decision. As a result, the image associated to the pruned tree represents a filtered or segmented version of the original image according to the selected criterion. Some of the criteria that are discussed in this work are based, for instance, on area, motion, marker \& propagation or a rate-distortion strategy. The problem of the lack of robustness of classical decision approaches of non-increasing criteria is discussed and solved by means of an optimization strategy based on the Viterbi algorithm. Content based image retrieval is the third application we have focused on in this work. Hierarchical region based representations are particularly well suited for this purpose since they allow to represent the image at different scales of resolution, and thus the regions of the image can be described at different scales of resolution. In this work we focus on an image retrieval system which supports low level queries based on visual descriptors and spatial relationships. For that purpose, region descriptors are attached to the nodes of the tree. Two types of queries are discussed: single region query, in which the query is made up of one region and, multiple region query, in which the query is made up of a set of regions. In the former visual descriptors are used to perform the retrieval whereas visual descriptors and spatial relationships are used in the latter case. Moreover, a relevance feedback approach is presented to avoid the need of manually setting the weights associated to each descriptor. An important aspect that has been taken into account throughout this work is the efficient implementation of the algorithms that have been developed for both creation and processing of the tree. In the case of the tree creation, efficiency has been obtained mainly due to the use of hierarchical queues, whereas in the processing step analysis algorithms based on recursive strategies are used to get efficient algorithms.

}, url = {http://hdl.handle.net/10803/6878}, author = {Garrido, L.}, editor = {Salembier, P.} } @book {eSalembier02, title = {Introduction to the mpeg-7: multimedia content description interface}, year = {2002}, publisher = {Wiley}, organization = {Wiley}, isbn = {0471486787}, author = {Manjunath, B.S and Salembier, P. and Sikora, T} } @inbook {bSalembier02a, title = {Overview of MPEG-7 multimedia description schemes and schema tools}, booktitle = {Introduction to the mpeg-7: multimedia content description interface}, year = {2002}, pages = {83{\textendash}94}, publisher = {Wiley}, organization = {Wiley}, edition = {B. S. Manjunath, P. Salembier, T. Sikora (Eds.)}, chapter = {6}, isbn = {0471486787}, author = {Salembier, P. and Smith, J.} } @article {aSalembier02a, title = {Overview of the MPEG-7 Standard and of Future Challenges for Visual Information Analysis}, journal = {EURASIP Journal on Applied Signal Processing}, volume = {4}, number = {1}, year = {2002}, pages = {1{\textendash}11}, issn = {0165-1684}, author = {Salembier, P.} } @book {eSayrol02, title = {Senyals i sistemes anal{\`o}gics: una introducci{\'o} pr{\`a}ctica}, year = {2002}, isbn = {84-8301-610-9}, url = {http://www.edicionsupc.es}, author = {Elisa Sayrol and Gasull, A. and Moreno, A. and Salavedra, J. and Vallverdu, F.} } @inbook {bSalembier02, title = {Systems Architecture}, booktitle = {Introduction to the mpeg-7: multimedia content description interface}, year = {2002}, pages = {33{\textendash}42}, publisher = {Wiley}, organization = {Wiley}, edition = {B. S. Manjunath, P. Salembier, T. Sikora (Eds.)}, chapter = {3}, isbn = {0471486787}, author = {Avaro, O. and Salembier, P.} } @article {aSalembier02, title = {Visual Segment Tree Creation for MPEG-7 Description Schemes}, journal = {Pattern recognition}, volume = {35}, number = {1}, year = {2002}, pages = {563{\textendash}579}, issn = {0031-3203}, author = {Salembier, P. and Llach, J. and Garrido, L.} } @conference {cSayrol01, title = {Color Inititialization for Lip Tracking}, booktitle = {International Conference on Augmented, Virtual Environments and 3D Imaging}, year = {2001}, pages = {351{\textendash}354}, author = {Elisa Sayrol and Fischi, O. and M. Pard{\`a}s} } @conference {cPineda01, title = {Estudio de campos de golf mediante t{\'e}cnicas de segmentaci{\'o}n}, booktitle = {IX Congreso Nacional de Teledetecci{\'o}n}, year = {2001}, address = {Lleida, Spain}, author = {Pineda, N and Jorge, J and Garrido, L. and Salembier, P.} } @conference {cSayrol01a, title = {Graphical Study of Signals and Systems}, booktitle = {International Conference on Acoustics, Speech and Signal Processing ICASSP{\textquoteright}01}, year = {2001}, isbn = {0-7803-1775-0}, author = {Elisa Sayrol and Gasull, A. and Moreno, A. and Salavedra, J. and Vallverdu, F.} } @article {aRuiz-Hidalgo01, title = {Morphological tools for robust key-region extraction and video shot modeling}, journal = {Lecture notes in computer science}, year = {2001}, pages = {407{\textendash}416}, abstract = {

In recent years, the use of multimedia content has experienced an exponential growth. In this context, the need of new image/video sequence representation is becoming a necessity for many applications. This paper deals with the structuring of video shots in terms\ of various foreground key-regions and a background mosaic. Each key-region represents different foreground objects that appear through the\ entire sequence in a similar manner the mosaic image represents the\ background information of the complete sequence. We focus on the interest of morphological tools such as connected operators or watersheds\ to perform the shot analysis and the computation of the key-regions and\ the mosaic. It will be shown that morphological tools are particularly attractive to improve the robustness of the various steps of the algorithm.

}, issn = {0302-9743}, author = {Ruiz-Hidalgo, J. and Salembier, P.} } @article {aPardas01, title = {Motion estimation based tracking of active contours}, journal = {Pattern recognition letters}, volume = {22}, year = {2001}, pages = {1447{\textendash}1456}, issn = {0167-8655}, author = {M. Pard{\`a}s and Elisa Sayrol} } @article {aSalembier01, title = {MPEG-7 Description Schemes}, journal = {IEEE transactions on circuits and systems for video technology}, volume = {11}, number = {6}, year = {2001}, pages = {748{\textendash}759}, issn = {1051-8215}, author = {Salembier, P. and Smith, J.} } @article {aAvaro01, title = {MPEG-7 Systems: overview}, journal = {IEEE transactions on circuits and systems for video technology}, volume = {11}, number = {6}, year = {2001}, pages = {760{\textendash}764}, issn = {1051-8215}, author = {Avaro, O. and Salembier, P.} } @conference {cSalembier01b, title = {MPEG-7: What{\textquoteright}s next for visual content representation and analysis?}, booktitle = {International Workshop on Very Low Bit Rate Video Coding 2001, VLBV 2001}, year = {2001}, address = {Athens, Greece}, author = {Salembier, P.} } @conference {cSalembier01a, title = {An overview of MPEG-7 Multimedia Description Schemes and of future visual information analysis challenges for content-based indexing}, booktitle = {International Workshop on Content-Based Multimedia Indexing, CBMI 2001}, year = {2001}, address = {Brescia, Italy}, author = {Salembier, P.} } @conference {cSalembier01, title = {An overview of the MPEG-7 standard and of future challenges for visual information analysis}, booktitle = {Workshop on Image Analysis for Multimedia Services, WIAMIS 2001}, year = {2001}, address = {Tampere, Finland}, author = {Salembier, P.} } @conference {cRuiz-Hidalgo01, title = {Robust segmentation and representation of foreground key-regions in video sequences}, booktitle = {International Conference on Acoustics, Speech and Signal Processing ICASSP{\textquoteright}01}, year = {2001}, month = {05/2001}, pages = {1565{\textendash}1568}, address = {Salt Lake City, USA}, author = {Ruiz-Hidalgo, J. and Salembier, P.} } @book {eSayrol01, title = {Senyals i sistemes anal{\`o}gics: una introducci{\'o} pr{\`a}ctica}, year = {2001}, isbn = {84-8301-510-2}, url = {www.edicionsupc.es}, author = {Elisa Sayrol and Gasull, A. and Moreno, A. and Salavedra, J. and Vallverdu, F.} } @conference {cSchelkens00, title = {3D compression of medical data based on cube-splitting and embedded block coding}, booktitle = {ProRISC/IEEE Workshop}, year = {2000}, month = {12/2000}, address = {Veldhoven, The Netherlands}, author = {Schelkens, P. and Xavier Gir{\'o}-i-Nieto and Barbarien, J. and Cornelis, J.} } @conference {cGasull00, title = {619 - un ejemplo de dise{\~n}o del laboratorio para asignaturas con cr{\'e}ditos te{\'o}ricos y pr{\'a}cticos}, booktitle = {VIII Congreso Universitario de Innovaci{\'o}n Educativa en las Ense{\~n}anzas T{\'e}cnicas}, year = {2000}, pages = {233{\textendash}240}, isbn = {84-7585-380-3}, author = {Gasull, A. and Moreno, A. and Salavedra, J. and Elisa Sayrol and Vallverdu, F.} } @conference {cEugenio00a, title = {Accurate and automatic NOAA-AVHRR image navigation using a global contour matching approach}, booktitle = {International Geoscience and remote Sensing Symposium}, year = {2000}, pages = {639{\textendash}642}, isbn = {0-7803-6362-0}, author = {F. Eugenio and Marqu{\'e}s, F. and G{\'o}mez, L. and Suarez, E. and Rovaris, E.} } @article {aSalembier00, title = {Binary partition tree as an efficient representation for image processing, segmentation and information retrieval}, journal = {IEEE transactions on image processing}, volume = {9}, number = {4}, year = {2000}, pages = {561{\textendash}576}, abstract = {

This paper discusses the interest of binary partition trees as a region-oriented image representation. Binary partition trees concentrate in a compact and structured representation a set of meaningful regions that can be extracted from an image. They offer a multiscale representation of the image and define a translation invariant 2-connectivity rule among regions. As shown in this paper, this representation can be used for a large number of processing goals such as filtering, segmentation, information retrieval and visual browsing. Furthermore, the processing of the tree representation leads to very efficient algorithms. Finally, for some applications, it may be interesting to compute the binary partition tree once and to store it for subsequent use for various applications. In this context, the paper shows that the amount of bits necessary to encode a binary partition tree remains moderate.

}, issn = {1057-7149}, doi = {10.1109/83.841934}, author = {Salembier, P. and Garrido, L.} } @conference {cSalembier00a, title = {Connected operators based on region-tree pruning}, booktitle = {Mathematical Morphology and its application to signal processing, ISMM 200}, year = {2000}, pages = {169{\textendash}184}, address = {Palo Alto, USA}, isbn = {0-7803-8555-1}, author = {Salembier, P. and Garrido, L.} } @conference {cSalembier00c, title = {Connected operators based on region-tree pruning strategies}, booktitle = {15th IAPR International Conference on Pattern Recognition, ICPR 2000}, year = {2000}, pages = {371{\textendash}374}, address = {Barcelona, Spain}, isbn = {?}, author = {Salembier, P. and Garrido, L.} } @conference {cEugenio00, title = {A contour matching approach for accurate NOAA-AVHRR image navigation}, booktitle = {10th European Signal Processing Conference (EUSIPCO 2000)}, year = {2000}, isbn = {952-15-0447-1}, author = {F. Eugenio and Marqu{\'e}s, F. and Suarez, E. and Rovaris, E.} } @conference {cSalembier00, title = {Creation of visual segment trees for MPEG-7 Description Schemes}, booktitle = {International Symposium on Image / video Communications over Fixed and Mobile Networks, ISIVC{\textquoteright}2000}, year = {2000}, pages = {127{\textendash}134}, address = {Rabat, Morocco}, isbn = {?}, author = {Salembier, P. and Llach, J. and Garrido, L.} } @conference {cVidal00, title = {Data Hidding in Color Images using Perceptual Models}, booktitle = {COST 254 Intelligent Processing and Facilities for Communications Terminals}, year = {2000}, pages = {21{\textendash}25}, author = {Vidal, J. and Elisa Sayrol and Maribel, M.} } @article {aSalembier00a, title = {Description Schemes for Video Programs, Users and Devices}, journal = {Signal processing: image communication}, volume = {16}, number = {1}, year = {2000}, pages = {211{\textendash}234}, issn = {0923-5965}, author = {Salembier, P. and Richard, Q. and O{\textquoteright}Connor, N. and Correia, P. and Sezan, I and van Beek, P} } @conference {cPardas00a, title = {A new approach to active contours for tracking}, booktitle = {IEEE International Conference on Image Processing}, year = {2000}, isbn = {0-7803-7403-7}, author = {M. Pard{\`a}s and Elisa Sayrol} } @inbook {bSalembier00, title = {Region-based filtering of images and video sequences: a morphological viewpoint}, booktitle = {Nonlinear Image Processing}, year = {2000}, publisher = {Academic Press}, organization = {Academic Press}, edition = {S. Mitra and G. Sicuranza (Eds.)}, chapter = {9}, isbn = {0125004516}, author = {Salembier, P.} } @conference {cMaziere00, title = {Segmentation and tracking of video objects for content-based video indexing}, booktitle = {IEEE International Conference on Multimedia and Expo, ICME{\textquoteright}2000}, year = {2000}, pages = {305{\textendash}309}, address = {New York City, NY, USA}, author = {Maziere, M. and Chassaing, F. and Garrido, L. and Salembier, P.} } @conference {cSayrol00, title = {Una Aproximaci{\'o}n experimental a las Se{\~n}ales y Sistemas Anal{\'o}gicos}, booktitle = {XV Simposium Nacional de la Uni{\'o}n Cient{\'\i}fica Internacional de Radio}, year = {2000}, pages = {329{\textendash}330}, isbn = {978-972-8865-74-0}, author = {Elisa Sayrol and Gasull, A. and Moreno, A. and Salavedra, J. and Vallverdu, F.} } @conference {cSalembier00b, title = {Visual Segment Tree Creation for MPEG-7 Description Schemes}, booktitle = {IEEE International Conference on Multimedia and Expo, ICME{\textquoteright}2000 }, year = {2000}, pages = {56{\textendash}61}, address = {New York City, NY, USA}, author = {Salembier, P. and Llach, J. and Garrido, L.} } @article {pSalembier99, title = {Analysis of Video Sequence. Method for Defining the Structure of a Video Sequence. Part I}, number = {994025948-}, year = {1999}, type = {Invention patent}, author = {Llach, J. and Salembier, P.} } @article {pSalembier99a, title = {Analysis of Video Sequence. Method for Defining the Structure of a Video Sequence. Part II}, number = {994026615-}, year = {1999}, type = {Invention patent}, author = {Llach, J. and Salembier, P.} } @conference {cLlach99, title = {Analysis of video sequences : table of content and index creation}, booktitle = {International Workshop on Very Low Bitrate Video, VLBV{\textquoteright}99}, year = {1999}, pages = {51{\textendash}54}, address = {Kobe, Japan}, author = {Llach, J. and Salembier, P.} } @conference {cSalembier99, title = {The DICEMAN description schemes for still images and video sequences}, booktitle = {Workshop on Image Analysis for Multimedia Application Services, WIAMIS{\textquoteright}99}, year = {1999}, pages = {25{\textendash}34}, address = {Berlin, Germany}, isbn = {84-7653-885-5}, author = {Salembier, P. and O{\textquoteright}Connor, N. and Correa, P. and Ward, L} } @conference {cGasull99, title = {Editor gr{\'a}fico de figuras MATLAB}, booktitle = {III Congreso de Usuarios de MATLAB}, year = {1999}, pages = {219{\textendash}227}, isbn = {84-699-1358-1}, author = {Gasull, A. and Elisa Sayrol and Moreno, A. and Vallverdu, F. and Salavedra, J. and Albert Oliveras} } @conference {cSalembier99a, title = {Hierarchical visual description schemes for still images and video sequences}, booktitle = {1999 IEEE International Conference on Image Processing, ICIP 1999}, year = {1999}, address = {Kobe, Japan}, author = {Salembier, P. and O{\textquoteright}Connor, N. and Correia, P. and Pereira, F.} } @conference {cVidal99, title = {Non-Noticeable Information Embedding in Color Images : Marking and Detection}, booktitle = {33rd ANNUAL - 1999 International Carnahan Conference on Security Technology}, year = {1999}, pages = {293{\textendash}297}, isbn = {0-7803-5247-5}, author = {Vidal, J. and Elisa Sayrol and Cabanillas, S. and Santamaria, S.} } @conference {cSayrol99, title = {Optimum Watermark Detection in Color Images}, booktitle = {1999 IEEE International Conference on Image Processing}, year = {1999}, pages = {1{\textendash}5}, author = {Elisa Sayrol and Vidal, J. and Cabanillas, S. and Santamaria, S.} } @article {aSalembier99, title = {Region-based representations of image and video : segmentation tools for multimedia services}, journal = {IEEE transactions on circuits and systems for video technology}, volume = {9}, number = {8}, year = {1999}, pages = {1147{\textendash}1169}, issn = {1051-8215}, author = {Salembier, P. and Marqu{\'e}s, F.} } @conference {cGarrido99, title = {Representing and retrieving regions using binary partition trees}, booktitle = {1999 IEEE International Conference on Image Processing, ICIP 1999}, year = {1999}, address = {Kobe, Japan}, isbn = {0-7803-5470-2}, author = {Garrido, L. and Salembier, P. and Casas, J.} } @conference {cSayrol99a, title = {Simulaci{\'o}n digital de se{\~n}ales y sistemas anal{\'o}gicos}, booktitle = {III Congreso de Usuarios de MATLAB}, year = {1999}, pages = {67{\textendash}76}, isbn = {84-699-1358-1}, author = {Sayrol E. and Gasull, A. and Moreno, A. and Vallverdu, F. and Salavedra, J. and Albert Oliveras} } @inbook {bMarques99, title = {Video compresssion standards}, booktitle = {Electronic imaging technology}, year = {1999}, pages = {31{\textendash}64}, publisher = {SPIE Optical Engineering Press}, organization = {SPIE Optical Engineering Press}, edition = {Edward R. Dougherty (Ed.)}, isbn = {0819430374}, author = {Marqu{\'e}s, F. and Salembier, P.} } @article {aSalembier98, title = {Antiextensive connected operators for image and sequence processing}, journal = {IEEE transactions on image processing}, volume = {7}, number = {4}, year = {1998}, pages = {555{\textendash}570}, abstract = {

This paper deals with a class of morphological operators called connected operators. These operators filter the signal by merging its flat zones. As a result, they do not create any new contours and are very attractive for filtering tasks where the contour information has to be preserved. This paper shows that connected operators work implicitly on a structured representation of the image made of flat zones. The max-tree is proposed as a suitable and efficient structure to deal with the processing steps involved in antiextensive connected operators. A formal definition of the various processing steps involved in the operator is proposed and, as a result, several lines of generalization are developed. First, the notion of connectivity and its definition are analyzed. Several modifications of the traditional approach are presented. They lead to connected operators that are able to deal with texture. They also allow the definition of connected operators with less leakage than the classical ones. Second, a set of simplification criteria are proposed and discussed. They lead to simplicity-, entropy-, and motion-oriented operators. The problem of using a nonincreasing criterion is analyzed. Its solution is formulated as an optimization problem that can be very efficiently solved by a Viterbi (1979) algorithm. Finally, several implementation issues are discussed showing that these operators can be very efficiently implemented.

}, issn = {1057-7149}, doi = {10.1109/83.663500}, url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=663500}, author = {Salembier, P. and Albert Oliveras and Garrido, L.} } @conference {cVidal98, title = {Autentificacion digital de imagen, marcado y detecci{\'o}n {\'o}ptimos}, booktitle = {XIII Simposium Nacional de la Uni{\'o}n Cient{\'\i}fica Internacional de Radio}, year = {1998}, pages = {105{\textendash}106}, isbn = {84-89654-12-3}, author = {Vidal, J. and Elisa Sayrol and Lagunas, M.} } @conference {cSalembier98, title = {Auto-dual connected operators based on iterative merging algorithms}, booktitle = {International Symposium on Mathematical Morphology and its applications to image and signal processing, ISMM 1998}, year = {1998}, pages = {183{\textendash}190}, address = {Amsterdam, The Netherlands}, isbn = {1522-4880}, author = {Salembier, P. and Garrido, L. and Garc{\'\i}a, D.} } @conference {cSalembier98b, title = {Binary partition tree as an efficient representation for filtering, segmentation and information retreival}, booktitle = {IEEE International Conference on Image Processing, ICIP 1998}, year = {1998}, address = {Chicago (IL), USA}, author = {Salembier, P. and Garrido, L.} } @inbook {bTorres98, title = {Codificaci{\'o}n de imagen}, booktitle = {Reconocimiento de formas y an{\'a}lisis de im{\'a}genes}, year = {1998}, pages = {101{\textendash}135}, publisher = {AERFAI}, organization = {AERFAI}, edition = {A. Sanfeliu (Ed.)}, isbn = {84-922529-4-4}, author = {Torres, L. and Salembier, P.} } @conference {cSalembier98a, title = {Connected operators for sprite creation and layered representation of image sequences}, booktitle = {9th European Signal Processing Conference, EUSIPCO 1998}, year = {1998}, pages = {2105{\textendash}2108}, address = {Rhodes, Greece}, isbn = {978-1-4503-0159-6}, author = {Salembier, P. and Pujol, O. and Garrido, L.} } @article {aGarrido98, title = {Extensive Operators in Partition Lattices for Image Sequence Analysis}, journal = {Signal processing}, volume = {66}, number = {2}, year = {1998}, pages = {157{\textendash}180}, issn = {0165-1684}, author = {Garrido, L. and Salembier, P. and Garc{\'\i}a, D.} } @conference {cVidal98a, title = {Optimum Watermark Detection and Embedding in Digital Images}, booktitle = {1998 IEEE Second Workshop on Multimedia Signal Processing}, year = {1998}, pages = {285{\textendash}290}, isbn = {0-7803-4919-9}, author = {Vidal, J. and Elisa Sayrol} } @conference {cGarrido98, title = {Region-based analysis of video sequences with a general merging algorithm}, booktitle = {9th European Signal Processing Conference, EUSIPCO 1998}, year = {1998}, pages = {1693{\textendash}1696}, address = {Rhodes, Greece}, isbn = {960-7620-06-4}, author = {Garrido, L. and Salembier, P.} } @conference {cVilaplana98, title = {Region-based segmentation segmentation and tracking of human faces}, booktitle = {9th European Signal Processing Conference, EUSIPCO 1998}, year = {1998}, pages = {311{\textendash}314}, address = {Rhodes, Greece}, isbn = {960-7620-06-4}, author = {Ver{\'o}nica Vilaplana and Marqu{\'e}s, F. and Salembier, P. and Garrido, L.} } @conference {cGarrido97a, title = {Anti-extensive Connected Operators with Application to Image Sequences}, booktitle = {VII Simposium Nacional de Reconocimiento de Formas y An{\'a}lisis de Im{\'a}genes}, year = {1997}, pages = {151{\textendash}156}, address = {Barcelona, Spain}, isbn = {84-922529-0-1}, author = {Garrido, L. and Salembier, P. and Albert Oliveras} } @phdthesis {dOliveras97, title = {Contribuci{\'o} a l{\textquoteright}an{\`a}lisi morfol{\`o}gica d{\textquoteright}imatges amb operadors connexes}, year = {1997}, school = {Universitat Polit{\`e}cnica de Catalunya (UPC)}, type = {phd}, author = {Albert Oliveras}, editor = {Salembier, P.} } @article {aMarques97, title = {General requirements for coding oriented segmentation of video sequences}, journal = {Annales des t{\'e}lecommunications. Annals of telecommunications}, volume = {52}, number = {7-8}, year = {1997}, pages = {359{\textendash}366}, issn = {0003-4347}, author = {Marqu{\'e}s, F. and Meyer, F. and M. Pard{\`a}s and Salembier, P.} } @conference {cGarrido97b, title = {A hierarchical technique for image sequence analysis}, booktitle = {Workshop on Image Analysis for Multimedia Application Services, WIAMIS{\textquoteright}97}, year = {1997}, pages = {13{\textendash}20}, address = {Louvain-la-Neuve, Belgium}, author = {Garrido, L. and Marqu{\'e}s, F. and M. Pard{\`a}s and Salembier, P. and Ver{\'o}nica Vilaplana} } @conference {cSalembier97, title = {Image sequence analysis and merging algorithms}, booktitle = {International Workshop on Very Low Bit-rate Video, VLBV{\textquoteright}97}, year = {1997}, pages = {1{\textendash}8}, address = {Link{\"o}ping, Sweden}, isbn = {0-7803-9752-5}, author = {Salembier, P. and Garrido, L. and Garc{\'\i}a, D.} } @article {aMeyer97, title = {Morphological tools for segmentation: connected operators and watersheds}, journal = {Annales des t{\'e}lecommunications. Annals of telecommunications}, volume = {52}, number = {7-8}, year = {1997}, pages = {366{\textendash}379}, issn = {0003-4347}, author = {Meyer, F. and Albert Oliveras and Salembier, P. and Vachier, C.} } @conference {cGarrido97, title = {Motion analysis of image sequences using connected operators}, booktitle = {SPIE Visual Communications and Image Processing, VCIP{\textquoteright}97}, year = {1997}, pages = {546{\textendash}557}, address = {San Jose, CA, USA}, isbn = {0-8194-2435-8}, author = {Garrido, L. and Albert Oliveras and Salembier, P.} } @conference {cSalembier97a, title = {Robust motion estimation using connected operators}, booktitle = {IEEE International Conference on Image Processing, ICIP{\textquoteright}97}, year = {1997}, pages = {77{\textendash}80}, address = {Santa Barbara, USA}, isbn = {1522-4880}, author = {Salembier, P. and Sanson, H.} } @article {aMarcotegui97, title = {Segmentation of video sequences and rate control}, journal = {Annales des t{\'e}lecommunications. Annals of telecommunications}, volume = {52}, number = {7-8}, year = {1997}, pages = {380{\textendash}388}, issn = {0003-4347}, author = {Marcotegui, B. and Marqu{\'e}s, F. and Morros, J.R. and M. Pard{\`a}s and Salembier, P.} } @article {aPardas97a, title = {Segmentation of video sequences for partition tree generation}, journal = {Annales des t{\'e}lecommunications. Annals of telecommunications}, volume = {52}, number = {7-8}, year = {1997}, pages = {389{\textendash}396}, issn = {0003-4347}, author = {M. Pard{\`a}s and Salembier, P.} } @article {aSalembier97, title = {Segmentation-based video coding system allowing the manipulation of objects}, journal = {IEEE transactions on circuits and systems for video technology}, volume = {7}, number = {1}, year = {1997}, pages = {60{\textendash}74}, issn = {1051-8215}, doi = {10.1109/76.554418}, author = {Salembier, P. and Marqu{\'e}s, F. and M. Pard{\`a}s and Morros, J.R. and Corset, I. and Jeannin, S. and Bouchard, L. and Meyer, F. and Marcotegui, B.} } @conference {cOliveras97, title = {Stereo image analyis using connected operators}, booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1997}, year = {1997}, pages = {3169{\textendash}3172}, address = {Munich, Germany}, isbn = {978-989-8109-05-7}, author = {Albert Oliveras and Garrido, L. and Salembier, P.} } @article {pPardas97, title = {Video coding method and corresponding coding and decoding systems}, number = {9693276.5-}, year = {1997}, type = {Invention patent}, author = {M. Pard{\`a}s and Salembier, P. and Ayuso, X. and Mart{\'\i}, E.} } @conference {cSalembier96d, title = {Active mesh coding and rate distortion theory}, booktitle = {IEEE International Conference on Image Processing, ICIP 1996}, year = {1996}, address = {Lausanne, Switzerland}, isbn = {0-7803-7043-0}, author = {Salembier, P. and Mart{\'\i}, E. and M. Pard{\`a}s} } @inbook {bSalembier96, title = {Coding of partition sequences}, booktitle = {Video coding: the second generation approach}, year = {1996}, pages = {125{\textendash}170}, publisher = {Kluwer}, organization = {Kluwer}, edition = {L. Torres and M. Kunt (Eds.)}, isbn = {0 7923 9680 4}, author = {Salembier, P. and Marqu{\'e}s, F. and Gasull, A.} } @inbook {bMarques96, title = {Coding-oriented segmentation of video sequences}, booktitle = {Video coding: the second generation approach}, year = {1996}, pages = {79{\textendash}124}, publisher = {Kluwer}, organization = {Kluwer}, edition = {L. Torres and M. Kunt (Eds.)}, isbn = {0 7923 9680 4}, author = {Marqu{\'e}s, F. and M. Pard{\`a}s and Salembier, P.} } @article {pOliveras96, title = {Filtering Method and Corresponding Filtering System}, number = {96402925.0-}, year = {1996}, type = {Invention patent}, author = {Albert Oliveras and Salembier, P. and Garrido, L.} } @conference {cOliveras96, title = {Generalized connected operators}, booktitle = {SPIE Visual Communication and Image Processing, VCIP{\textquoteright}96}, year = {1996}, pages = {2727{\textendash}2771}, address = {Orlando, Florida, USA}, author = {Albert Oliveras and Salembier, P.} } @article {aSalembier96, title = {Morphological operators for image and video compression}, journal = {IEEE transactions on image processing}, volume = {5}, number = {6}, year = {1996}, month = {06/1996}, pages = {881{\textendash}898}, abstract = {

This paper deals with the use of some morphological tools for image and video coding. Mathematical morphology can be considered as a shape-oriented approach to signal processing, and some of its features make it very useful for compression. Rather than describing a coding algorithm, the purpose of this paper is to describe some morphological tools that have proved attractive for compression. Four sets of morphological transformations are presented: connected operators, the region-growing version of the watershed, the geodesic skeleton, and a morphological interpolation technique. The authors discuss their implementation, and show how they can be used for image and video segmentation, contour coding, and texture coding.

}, issn = {1057-7149}, doi = {10.1109/83.503906}, author = {Salembier, P. and Brigger, P. and Casas, J. and M. Pard{\`a}s} } @conference {cSalembier96e, title = {Morphological operators for very low bit rate video coding}, booktitle = {IEEE International Conference on Image Processing, ICIP 1996}, year = {1996}, pages = {659{\textendash}662}, address = {Lausanne, Switzerland}, isbn = {0-8194-5654-3}, author = {Salembier, P. and Meyer, F. and Brigger, P. and Bouchard, L.} } @conference {cSalembier96, title = {Motion compensated partition coding}, booktitle = {SPIE Visual Communication and Image Processing, VCIP{\textquoteright}96}, year = {1996}, pages = {403{\textendash}415}, address = {Orlando, Florida, USA}, isbn = {84-699-1359-1}, author = {Salembier, P.} } @conference {cSalembier96b, title = {Motion connected operators for image sequences}, booktitle = {VIII European Signal Processing Conference, EUSIPCO{\textquoteright}96}, year = {1996}, pages = {1083{\textendash}1086}, address = {Trieste, Italy}, isbn = {84-600-9597-5}, author = {Salembier, P. and Albert Oliveras and Garrido, L.} } @article {aSayrol96, title = {Motion estimation using higher-order statistics}, journal = {IEEE transactions on image processing}, volume = {5}, number = {6}, year = {1996}, pages = {1077{\textendash}1084}, issn = {1057-7149}, author = {Elisa Sayrol and Gasull, A. and R. Fonollosa, Javier} } @conference {cPardas96, title = {Partition tree for a segmentation-based video coding system}, booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1996}, year = {1996}, pages = {1982{\textendash}1985}, address = {Atlanta (GA), USA}, isbn = {-}, author = {M. Pard{\`a}s and Salembier, P. and Marqu{\'e}s, F. and Morros, J.R.} } @conference {cOliveras96b, title = {Practical extensions of connected operators}, booktitle = {International Symposium on Mathematical Morphology, ISMM 1996}, year = {1996}, pages = {97{\textendash}110}, address = {Atlanta (GA), USA}, author = {Salembier, P. and Albert Oliveras} } @conference {cMarques96, title = {A segmentation-based coding system allowing manipulation of objects}, booktitle = {IEEE International Conference on Image Processing, ICIP 1996}, year = {1996}, pages = {145{\textendash}175}, address = {Lausanne, Switzerland}, abstract = {

We present a coding scheme that achieves, for each image in the sequence, the best segmentation in terms of rate-distortion theory. It is obtained from a set of initial regions and a set of available coding techniques. The segmentation combines spatial and motion criteria. It selects at each area of the image the most adequate criterion for defining a partition in order to obtain the best compromise between cost and quality. In addition, the proposed scheme is very suitable for addressing content-based functionalities.

}, isbn = {0-7803-3258-X}, doi = {10.1109/ICIP.1996.560741}, author = {Marqu{\'e}s, F. and Salembier, P. and M. Pard{\`a}s and Morros, J.R. and Corset, I. and Jeannin, S. and Marcotegui, B. and Meyer, F.} } @conference {cSalembier96c, title = {Segmentation-based video coding: temporal links and rate control}, booktitle = {VIII European Signal Processing Conference, EUSIPCO{\textquoteright}96}, year = {1996}, pages = {455{\textendash}458}, address = {Trieste, Italy}, author = {Salembier, P. and Marqu{\'e}s, F. and M. Pard{\`a}s} } @article {pSalembier96a, title = {Segmented Picture Coding Method and System and Corresponding Decoding Method and System}, number = {964009161-}, year = {1996}, type = {Invention patent}, author = {Salembier, P. and Marqu{\'e}s, F. and Corset, I. and Bouchard, L. and Jeannin, S. and M. Pard{\`a}s and Morros, J.R. and Meyer, F. and Marcotegui, B.} } @inbook {bCasas96c, title = {Strong edge features for image coding}, booktitle = {Mathematical Morphology and its Applications to Image and Signal Processing}, volume = {5}, year = {1996}, pages = {443{\textendash}450}, publisher = {Springer}, organization = {Springer}, address = {Boston}, abstract = {

A two component model is proposed for perceptual image coding For the first component of the model the watershed operator is used to detect strong edge features Then an efficientmorphological interpolation algorithm reconstructs the smooth areas of the image from the extracted edge information also known as sketch data The residual component containing ne textures is separately coded by a subband coding scheme The morphological operators involved in the coding of the primary component perform very e ciently compared to conventional techniques like the LGO operator used for the edge extraction or the di usion lters iteratively applied for the interpolation of smooth areas in previously reported sketch based coding schemes.

}, isbn = {0-793-9733-9}, doi = {10.1007/978-1-4613-0469-2_52}, author = {Casas, J. and Torres, L.}, editor = {Schafer, R. W. and Maragos, P. and Butt, M. A.} } @conference {cSalembier96a, title = {Very low rate video coding using active triangular mesh}, booktitle = {IEEE International Conference on Acoustics, Speech \& Signal Processing, ICASSP 1996}, year = {1996}, pages = {97{\textendash}110}, address = {Atlanta (GA), USA}, isbn = {84-699-1358-1}, author = {Salembier, P. and Ayuso, X.} } @conference {cMorros96, title = {Video sequence segmentation based on rate-distortion theory}, booktitle = {SPIE Visual Communication and Image Processing, VCIP{\textquoteright}96}, year = {1996}, month = {02/1996}, publisher = {Proc. SPIE 2727, 1185}, organization = {Proc. SPIE 2727, 1185}, address = {Orlando, Florida, USA}, abstract = {
This paper describes a coding-oriented segmentation technique for video schemes using an optimization strategy to address the problem of bit allocation. The optimization is based on the rate-distortion theory. Our purpose is to define a method to obtain an {\textquoteright}optimal{\textquoteright} partition together with the best coding technique for each region of this partition so that the result is optimal in a rate-distortion sense.

}, author = {Morros, J.R. and Marqu{\'e}s, F. and M. Pard{\`a}s and Salembier, P.} } @conference {cSayrol95a, title = {Estimation of motion parameters using hos}, booktitle = {IEEE SIGNAL PROCESSING-ATHOD WORKSHOP ON HIGHER-ORDER STATISTICS.}, year = {1995}, pages = {262{\textendash}265}, isbn = {1522-4880}, author = {Elisa Sayrol and Gasull, A. and R. Fonollosa, Javier} } @article {aSalembier95a, title = {Flat zones filtering, connected operators and filters by reconstruction}, journal = {IEEE transactions on image processing}, volume = {3}, number = {8}, year = {1995}, pages = {1153{\textendash}1160}, issn = {1057-7149}, author = {Salembier, P. and Serra, J.} } @conference {cSayrol95, title = {Fourth-order statistics cost functions: applications to time delay estimation and image motion estimation}, booktitle = {VI SPANISH SYMPOSIUM ON PATTERN RECOGNITION AND IMAGE ANALYSIS}, year = {1995}, pages = {543{\textendash}548}, isbn = {978-1-4244-9564-1}, author = {Elisa Sayrol and Gasull, A. and R. Fonollosa, Javier} } @article {aSayrol95, title = {Image Restoration using the W-Slice Method}, journal = {IEEE transactions on image processing}, volume = {4}, number = {4}, year = {1995}, pages = {1174{\textendash}1181}, abstract = {

We propose the use of higher order statistics (HOS)-based methods to address the problem of image restoration. The restoration strategy is based on the fact that the phase information of the original image and its HOS are not distorted by some types of blurring. The difficulties associated with the combination of 2-D signals and their HOS are reduced by means of the Radon transform. Two methods that apply the weight-slice algorithm over the projections are developed. Simulation results illustrate the performance of the proposed methods

}, issn = {1057-7149}, author = {Elisa Sayrol and Gasull, A. and Nikias, C.} } @article {pSalembier95, title = {Method of Coding an Image Sequence}, number = {954018131-}, year = {1995}, type = {Invention patent}, author = {Salembier, P.} } @article {pSalembier95a, title = {Method of Coding an Image Sequence and Corresponding Decoding Method}, number = {954020202-}, year = {1995}, type = {Invention patent}, author = {Salembier, P.} } @conference {cCasas95, title = {Morphological interpolation for texture coding}, booktitle = {IEEE International Conference on Image Processing, ICIP 1995}, year = {1995}, pages = {903{\textendash}907}, address = {Washington DC, USA}, abstract = {

In this paper a new morphological interpolation technique is presented. It is applied to the coding of the smooth (primary) component in a sketch-based image compression approach for very low bit-rates. The interpolation technique is intended to perform two dimensional interpolation from any set of initial pixels and, in particular, from sketch data. It makes intensive use of geodesic dilation, a morphological operator that may be implemented by means of FIFO queues. This results in a very efficient process compared to those that perform interpolation by linear filtering on the initial image. For the application of this method to interpolative image coding, the sketch data is extracted as a set of maximum curvature lines by means of the watershed algorithm. From such information, the interpolation technique obtains a fair reconstruction of both the smooth texture component and the main transitions of the image signal at low bit-rate cost.

}, author = {Casas, J. and Salembier, P. and Torres, L.} } @article {aSalembier95, title = {Region-based video coding using mathematical morphology}, journal = {Proceedings of the IEEE}, volume = {83}, number = {6}, year = {1995}, pages = {843{\textendash}857}, issn = {0018-9219}, author = {Salembier, P. and Torres, L. and Meyer, F. and Gu, C.} } @phdthesis {dPardas95, title = {Segmentaci{\'o}n Morfol{\'o}gica de Secuencias de Im{\'a}genes: Aplicaci{\'o}n a la Codificaci{\'o}n}, year = {1995}, school = {Universitat Polit{\`e}cnica de Catalunya (UPC)}, type = {phd}, author = {M. Pard{\`a}s}, editor = {Salembier, P.} } @conference {cSalembier95 , title = {Texture coding using morphological interpolation}, booktitle = {IEEE workshop on Nonlinear Signal and Image Processing, NSIP 1995}, year = {1995}, address = {Halkidiki, Greece}, author = {Salembier, P. and Ru{\'e}, R} } @article {aPardas94, title = {3d morphological segmentation and motion estimation for image sequences}, journal = {Signal processing}, volume = {38}, number = {2}, year = {1994}, pages = {31{\textendash}43}, issn = {0165-1684}, author = {M. Pard{\`a}s and Salembier, P.} } @article {aSalembier94, title = {Hierarchical morphological segmentation for image sequence coding}, journal = {IEEE transactions on image processing}, volume = {3}, number = {5}, year = {1994}, pages = {639{\textendash}651}, issn = {1057-7149}, author = {Salembier, P. and M. Pard{\`a}s} } @phdthesis {dSayrol94, title = {Higher-order statistics applications in image sequence processing}, year = {1994}, school = {Universitat Polit{\`e}cnica de Catalunya (UPC)}, type = {phd}, url = {http://hdl.handle.net/10803/6950}, author = {Elisa Sayrol}, editor = {Gasull, A.} } @conference {cMarques94c, title = {Interleaved segmentation and motion estimation by means of morphological tools}, booktitle = {Workshop on Image Analysis and Synthesis in Image Coding}, year = {1994}, address = {Berlin, Germany}, author = {Marqu{\'e}s, F. and Bouchard, L. and Corset, I. and Jeannin, S. and Morros, J.R. and M. Pard{\`a}s and Salembier, P. and Torres, L.} } @conference {cPardas94b, title = {Joint region and motion estimation with morphological tools}, booktitle = {International Symposium on Mathematical Morphology, ISMM 1994}, year = {1994}, address = {Fontainebleau, France}, author = {M. Pard{\`a}s and Salembier, P.} } @article {aSalembier94a, title = {Morphological multiscale segmentation for image coding}, journal = {Signal processing}, volume = {38}, number = {3}, year = {1994}, pages = {359{\textendash}386}, issn = {0165-1684}, author = {Salembier, P.} } @inbook {bCasas94, title = {Morphological scheme for morphometric analysis of epidermal biopsy images}, booktitle = {Mathematical Morphology and its Applications to Image Processing}, volume = {2}, number = {Computational Imaging and Vision}, year = {1994}, pages = {325{\textendash}331}, publisher = {Springer}, organization = {Springer}, address = {Dordrecht}, abstract = {

This paper addresses the problem of morphometric analysis of microscope images from cutaneous biopsy samples. A morphological scheme is applied for the automatic measurement of histologic parameters of the epidermis. It consists in an unsupervised segmentation approach that is strongly based on an {\textquoteright}a priori{\textquoteright} model of the images. The watershed algorithm has proven to be a very powerful tool for the introduction of such {\textquoteright}a priori{\textquoteright} information, because the segmentation process can be conveniently guided by some strategic markers in order to perform the detection of the desired structures. This permits an automatic measurement of some objective parameters which are highly correlated with the evolution of some skin diseases.

}, doi = {10.1007/978-94-011-1040-2_42}, author = {Casas, J. and Esteban, P. and Moreno, A. and Carrera, M.}, editor = {Serra, J. and Soille, P.} } @conference {cPardas94a, title = {Motion region overlapping for segmentation-based video coding}, booktitle = {International Conference on Image Processing, ICIP{\textquoteright}94}, year = {1994}, pages = {428{\textendash}431}, address = {Austin, Texas}, isbn = {0-7803-5470-2}, author = {M. Pard{\`a}s and Salembier, P. and Gonzalez, B.} } @conference {cSerra94 , title = {Op{\'e}rateurs connexes et pyramides}, booktitle = {In Proc. of RFIA}, year = {1994}, address = {Paris, France}, author = {Serra, J. and Salembier, P.} } @conference {cSalembier94 , title = {Self-referred texture coding for segmentation-based codec}, booktitle = {SPIE Visual Communication and Image Processing, VCIP{\textquoteright}94}, year = {1994}, address = {Chicago (IL), USA}, author = {Salembier, P. and Lopez, F} } @conference {cPardas94, title = {Time-recursive segmentation of image sequences}, booktitle = {European Signal Processing Conference, EUSIPCO-94}, year = {1994}, pages = {18{\textendash}21}, address = {Edinburgh, UK}, author = {M. Pard{\`a}s and Salembier, P.} } @conference { cSalembier94, title = {Very low bit rate video coding using morphological segmentation and contour/texture motion compensation}, booktitle = {12th International Conference on Pattern Recognition, ICPR 1994}, year = {1994}, address = {Jerusalem, Israel}, author = {Salembier, P. and Gu, C. and M. Pard{\`a}s and Kunt, M} } @conference {cPardas93a, title = {3D morphological segmentation and motion estimation for image sequences}, booktitle = {International Symposium on Mathematical Morphology and its applications to image and signal processing, ISMM 1993}, year = {1993}, pages = {58{\textendash}63}, address = {Barcelona, Spain}, isbn = {0-8186-8821-1}, author = {M. Pard{\`a}s and Salembier, P.} } @conference {cPardas93, title = {3D morphological segmentation or image sequence processing}, booktitle = {IEEE Winter Workshop on Nonlinear Signal Processing}, year = {1993}, pages = {31{\textendash}36}, address = {Tampere, Finland}, isbn = {960-7620-06-4}, author = {M. Pard{\`a}s and Salembier, P. and Torres, L.} } @conference {cSalembier93a, title = {Application of mathematical morphology to picture coding}, booktitle = {General Assembly of URSI, 1993}, year = {1993}, address = {Kyoto, Japan}, author = {Salembier, P.} } @conference {cSerra93, title = {Connected operators and pyramids}, booktitle = {SPIE Image Algebra and Mathematical Morphology}, year = {1993}, pages = {65{\textendash}76}, address = {San Diego (CA), USA}, isbn = {1522-4880}, author = {Serra, J. and Salembier, P.} } @conference {cSalembier93c, title = {Edge versus contrast estimation of morphological filters}, booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1993}, year = {1993}, address = {Mineapolis (MI), USA}, author = {Salembier, P. and Serra, J. and Bangham, J.} } @conference {cSayrol93a, title = {Image analysis using higher-order statistics and the radon transfrom}, booktitle = {IEEE SIGNAL PROCESSING WORKSHOP ON HIGH-ORDER-STATISTICS}, year = {1993}, pages = {76{\textendash}80}, author = {Elisa Sayrol and Nikias, C. and Gasull, A.} } @conference {cSayrol93, title = {Image analysis using higher-order statistics and the random transfor}, booktitle = {WORKSHOP ON HIGHER-ORDER STATISTICS}, year = {1993}, author = {Elisa Sayrol and Gasull, A.} } @book {eSalembier93, title = {Mathematical morphology and its applications to signal processing}, year = {1993}, publisher = {Universitat Polit{\`e}cnica de Catalunya (UPC)}, organization = {Universitat Polit{\`e}cnica de Catalunya (UPC)}, address = {Barcelona}, isbn = {8476532717}, author = {Serra, J. and Salembier, P.} } @conference {cSalembier93b, title = {Morphological approach to segmentation-based image coding}, booktitle = {Picture Coding Symposium, PCS 1993}, year = {1993}, pages = {121{\textendash}122}, address = {Lausanne, Switzerland}, isbn = {0-7803-1238-4}, author = {Salembier, P.} } @conference {cMarques93c, title = {Morphological scheme for myalinated nerve fiber morphometric analysis}, booktitle = {International Symposium on Mathematical Morphology and its applications to image and signal processing, ISMM 1993}, year = {1993}, pages = {122{\textendash}126}, address = {Barcelona, Spain}, url = {Problemes de connexi{\'o} a l{\textquoteright}Eprints}, author = {Marqu{\'e}s, F. and Salembier, P. and Navarro, X. and Sa{\~n}udo, J.} } @conference {cSalembier93f, title = {Morphological segmentation-based coding of image sequences}, booktitle = {IEEE European Conference on Circuits Theory and Design}, year = {1993}, pages = {1245{\textendash}1250}, address = {Davos, Switzerland}, isbn = {0-7803-5470-2}, url = {Problemes de connexi{\'o} a l{\textquoteright}Eprints}, author = {Salembier, P. and Torres, L. and M. Pard{\`a}s and Marqu{\'e}s, F. and HIERRO, P. and Gasull, A.} } @conference {cSalembier93d, title = {Multi-criterion segmentation for image coding}, booktitle = {International Symposium on Mathematical Morphology and its applications to image and signal processing, ISMM 1993}, year = {1993}, pages = {40{\textendash}45}, address = {Barcelona, Spain}, author = {Salembier, P.} } @conference {cSalembier93e, title = {Object-based image coding with morphological segmentation and efficient contour coding}, booktitle = {IEEE International Conference on Signal Processing, ICSP{\textquoteright}93}, year = {1993}, address = {Beijing, China}, author = {Salembier, P. and Marqu{\'e}s, F.} } @conference {cSalembier93, title = {Unsupervised morphological segmentation for images}, booktitle = {IEEE Winter Workshop on Nonlinear Signal Processing}, year = {1993}, pages = {21{\textendash}26}, address = {Tampere, Finland}, author = {Salembier, P.} } @conference {cSalembier92, title = {Adaptation of grey level structuring elements for morphological filters with application to shape detection}, booktitle = {VI European Signal Processing Conference, EUSIPCO{\textquoteright}92}, year = {1992}, pages = {1137{\textendash}1140}, address = {Brussels, Belgium}, isbn = {0-7803-8485-7}, author = {Salembier, P.} } @article {aSalembier92b, title = {Adaptive rank order based filters}, journal = {Signal processing}, volume = {27}, number = {1}, year = {1992}, pages = {1{\textendash}25}, issn = {0165-1684}, author = {Salembier, P.} } @conference {cSalembier92b, title = {Morphological detection based on size and contrast criteria}, booktitle = {14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society}, year = {1992}, pages = {1930{\textendash}1031}, address = {Paris, France}, isbn = {?}, author = {Salembier, P. and Gasull, A. and Marqu{\'e}s, F. and Elisa Sayrol} } @conference {cSalembier92a, title = {Morphological multiscale image segmentation}, booktitle = {SPIE Visual Communication and Image Processing, VCIP{\textquoteright}92}, year = {1992}, pages = {620{\textendash}631}, address = {Boston, USA}, author = {Salembier, P. and Serra, J.} } @article {aSalembier92a, title = {Size-sensitive multiresolution decomposition of images with rank..}, journal = {Signal processing}, volume = {27}, number = {2}, year = {1992}, pages = {205{\textendash}241}, issn = {0165-1684}, author = {Salembier, P.} } @article {aSalembier92, title = {Structuring element adaptation for morphological filters}, journal = {Journal of visual communication and image representation}, volume = {3}, number = {2}, year = {1992}, pages = {115{\textendash}136}, issn = {1047-3203}, author = {Salembier, P.} } @conference {cSalembier91, title = {Adaptive morphological multiresolution decomposition}, booktitle = {SPIE Image Algebra and Mathematical Morphology}, year = {1991}, pages = {620{\textendash}631}, address = {San Diego, USA}, author = {Salembier, P. and Jaquenoud, L} } @article {aSanz90, title = {Aspectos Cl{\'\i}nicos-toxicol{\'o}gicos en los trabajadores de una industria productora de cromatos}, journal = {Annual review of pharmacology and toxicology}, volume = {7}, year = {1990}, pages = {1:13{\textendash}1:20}, issn = {0362-1642}, author = {Sanz, P. and Ribas, B. and Cobo, E. and Gadea, E. and Marqu{\'e}s, F. and Sol{\'e}, E. and Corbella, J.} } @article {pSalembier89, title = {Appareil de D{\'e}codage de Signaux Modul{\'e}s en Fr{\'e}quence}, number = {8900812-}, year = {1989}, type = {Invention patent}, author = {Salembier, P. and Lamnabhi, M.} } @conference {cGasull89a, title = {Automated left ventricular contour extraction and volume calculation form echocardiographic images}, booktitle = {Ultrasonics International 89}, year = {1989}, pages = {1{\textendash}4}, isbn = {SN.}, author = {Gasull, A. and Alquezar, R. and Torres, L. and Sallent, S. and Marqu{\'e}s, F. and Vidal, J. and Sangr{\'a}, E.} } @conference {cVazquez89, title = {Constant variance transversal filtering for adaptive channel equalization}, booktitle = {INTERNATIONAL CONFERENCE ON SONAR SIGNAL PROCESSING}, year = {1989}, pages = {212{\textendash}215}, isbn = {0-7923-9733-9}, author = {Vazquez, G. and Gasull, A. and Sanchez, J. and Lagunas, M.} } @article {pSalembier88a, title = {Appareil Muni d{\textquoteright}un Dispositif de R{\'e}stitution de la Composante Continue Am{\'e}lior{\'e}}, number = {8814685-}, year = {1988}, type = {Invention patent}, author = {Salembier, P. and Hayet, P.} } @conference {cSallent88, title = {Codificaci{\'o}n piramidal generalizada}, booktitle = {III Simposium Nacional de Reconocimiento de Formas y An{\'a}lisis de Im{\'a}genes}, year = {1988}, pages = {1{\textendash}2}, isbn = {142440469X/1520-6149}, author = {Sallent, S. and Torres, L. and Gasull, A.} } @conference {cGasull88, title = {Detecci{\'o}n autom{\'a}tica de contornos en im{\'a}genes ecogr{\'a}ficas}, booktitle = {III Simposium Nacional de Reconocimiento de Formas y An{\'a}lisis de Im{\'a}genes}, year = {1988}, pages = {1{\textendash}4}, isbn = {?}, author = {Gasull, A. and Marqu{\'e}s, F. and Sallent, S. and Torres, L. and Vidal, J.} } @article {pSalembier88, title = {Dispositif de R{\'e}ception de Signaux Num{\'e}riques Cod{\'e}s et Modul{\'e}s en Fr{\'e}quences}, number = {8808919-}, year = {1988}, type = {Invention patent}, author = {Salembier, P. and Lamnabhi, M.} } @article {pSalembier87, title = {Dispositif d{\textquoteright}Am{\'e}lioration du D{\'e}codage de Signaux Num{\'e}riques lors de Transmission en Modulation de Fr{\'e}quence}, number = {8710580-}, year = {1987}, type = {Invention patent}, author = {Salembier, P. and Lamnabhi, M.} }