@conference {cDorca25, title = {Multimodal AI for Atypical Hyperplasia Diagnosis: A Comparative Study of CNNs, GNNs, and Hybrid Models}, 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 = {

The diagnosis of atypical hyperplasia in endometrial aspirates is complex due to morphological variations across the menstrual cycle, often leading to interobserver variability. This study explores the use of artificial intelligence to enhance diagnostic accuracy by developing an AI-assisted framework to improve reproducibility and clinical decision-making in gynecological pathology.

}, url = {https://www.ecdp2025.org/ecdp2025-program.pdf}, author = {Eduard Dorca and Oscar Pina and Maria del Rosario Taco and Esther Guerra Fermamdez and Ver{\'o}nica Vilaplana and August Vidal Bel} } @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 Josep R Casas 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 Josep R Casas and Santiago Royo} } @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 {xBarrabes22, title = {Machine Learning for Genomic Sequence Processing}, year = {2022}, abstract = {

Introduction to Research, BSc Data Science and Engineering, Autumn 2021:

Predicting Dog Phenotypes from Genotypes

In this paper, we analyze dog genotypes {\textendash} positions of DNA sequences that often vary between different dogs {\textendash}in order to predict the corresponding phenotypes {\textendash} unique characteristics that result from different genetic code. More specifically, given chromosome data from a dog, we aim to predict its breed category, height, and weight. We explore a variety of linear and non-linear classification and regression techniques to accomplish these three tasks. We also investigate the use of a neural network (both in linear and non-linear modes) for breed classification and compare its performance to traditional statistical methods. We show that linear methods generally outperform or match the performance of non-linear methods for breed classification. However, the reverse case is true for height and weight regression. We also evaluate the results of all of these methods based on the number of input features used in the analy sis and demonstrate that phenotypes can be predicted with as few as 0.5\% of the input features, and dog breeds can be classified with 50\% balanced accuracy with as few as 0.02\% of the full genomic sequences for our analysis.

MergeGenome. A Python-based Toolkit for Merging VCF files

A challenge of genomic studies is the lack of easy to access and properly formatted datasets. When having access to more than one dataset, it seems desirable to combine them. There is a lack of tools to duly merge genomic datasets without losing all non-matching features. To fill this gap, we present the MergeGenome toolkit, designed to integrate DNA sequences from two files in variant call format (VCF) while targeting data quality. MergeGenome is a robust pipeline of comprehensive steps to standardize nomenclature, remove ambiguities, correct flips, eliminate mismatches, select important features, and filter likely erroneous features (the latter with machine learning). MergeGenome is Python-based and relies on pre-existing software for manipulation and imputation of VCF data. We evaluate the result of merging two datasets with dog DNA sequences of dissimilar lengths and notice that genotype imputation with Beagle v5.1 usually fails for low-frequency alleles. Alternatively, we explore several multi-label machine learning classifiers. Although K-Nearest Neighbors achieves competitive results, none of the methods tried outperforms Beagle v5.1.

}, author = {Barrab{\'e}s, M{\'\i}riam}, editor = {Mas-Montserrat, Daniel and Xavier Gir{\'o}-i-Nieto and Ioannidis, Alexander G.} } @article {pTerradas22, title = {A method, system and computer programs to automatically transform an image}, journal = {European Patent Office}, volume = {21382176}, year = {2022}, abstract = {

The present invention is directed, in general, to a method and a system to automatically transform an image using neural networks. More specifically, the invention relates to a controllable image generation through an image representation and several conditions using a conditional Neural Network.

The method comprises receiving, by a processing unit, at least one image and processing the received image to obtain an image representation thereof (i.e. an intermediate representation of the initial image that captures high level features and low level properties of the image and that is structured in an understandable way for a conditional Neural Network such as a deep generative Neural Network). The method also includes receiving, by an encoding unit, one or more references (e.g. other images, text, labels, combinations thereof, or even other data describing how the received image should be transformed) and encoding the received one or more references into one or more features, the latter being further provided to a conditional Neural Network as a condition(s). In addition, the method further applies the conditional Neural Network to transform the obtained image representation into a resulting conditioned image based on said condition(s).

}, issn = {21382176.2}, url = {https://patentscope.wipo.int/search/es/detail.jsf?docId=EP373278976}, author = {Terradas, R. and Pau Domingo and Grau, M. and Alarc{\'o}n, E. and Ruiz-Hidalgo, J.} } @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 {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} } @article {xBudria22, title = {Multimodal 3D Hand Pose Enhancement for Sign Language}, year = {2022}, abstract = {

The application of recent deep learning breakthroughs to the domain of sign language has yielded very promising results. However, sign language processing systems depend on large amounts of labeled high-quality data to work properly. Current hand pose estimation methods are often unreliable and do not always produce estimations with enough quality. To mitigate this issue, we explore the applicability of the novel Body2Hands method for the obtainment of high-quality hand pose estimations.

}, author = {{\'A}lvaro Budria}, editor = {Laia Tarr{\'e}s and Moreno, Francesc and Xavier Gir{\'o}-i-Nieto} } @conference {cGarcia-Gomez22, title = {Multimodal imaging System based on solid-State LiDAR for Advanced perception applications}, booktitle = {10th International Symposium on Optronics in defence \& security}, year = {2022}, month = {06/2022}, publisher = {3AF OPTRO2022}, organization = {3AF OPTRO2022}, address = {Versailles, France}, url = {https://www.3af-optro.com/}, author = {Pablo Garc{\'\i}a-G{\'o}mez and S. Royo and Noel Rodrigo and Josep R Casas and Jordi Riu} } @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} } @inbook {bMora, title = {MRI brain tumor segmentation and uncertainty estimation using 3D-UNet architectures}, booktitle = {Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2020}, volume = {12658}, number = {Lecture Notes in Computer Science}, year = {2021}, pages = {376-390}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, abstract = {

Automation of brain tumor segmentation in 3D magnetic resonance images (MRIs) is key to assess the diagnostic and treatment of the disease. In recent years, convolutional neural networks (CNNs) have shown improved results in the task. However, high memory consumption is still a problem in 3D-CNNs. Moreover, most methods do not include uncertainty information, which is especially critical in medical diagnosis. This work studies 3D encoder-decoder architectures trained with patch-based techniques to reduce memory consumption and decrease the effect of unbalanced data. The different trained models are then used to create an ensemble that leverages the properties of each model, thus increasing the performance. We also introduce voxel-wise uncertainty information, both epistemic and aleatoric using test-time dropout (TTD) and data-augmentation (TTA) respectively. In addition, a hybrid approach is proposed that helps increase the accuracy of the segmentation. The model and uncertainty estimation measurements proposed in this work have been used in the BraTS{\textquoteright}20 Challenge for task 1 and 3 regarding tumor segmentation and uncertainty estimation.

}, isbn = {978-3-030-72083-4}, issn = {978-3-030-72084-1}, doi = {https://doi.org/10.1007/978-3-030-72084-1_34}, author = {Laura Mora and Ver{\'o}nica Vilaplana} } @conference {cGarcia-Gomez21, title = {Multimodal solid-state LiDAR for advanced perception applications}, booktitle = {OPTOEL}, year = {2021}, month = {06/2021}, abstract = {

Perception of the environment is an essential requirement for the fields of autonomous vehicles and robotics. Consequently, LiDAR imaging sensors have become crucial sen-sors for such applications due to their 3D geometry sensing capability. However, auton-omous systems claim for high amounts of data to make reliable decisions so many dif-ferent sensors are often combined. In this context, we present a multimodal imaging sys-tem based on a solid-state LiDAR combined with three other imaging sensors that pro-vides multimodal information with low parallax fusion error.

}, keywords = {artificial intelligence, autonomous navigation, computer Vision, enhanced perception, robotics, sensor fusion, solid-state LiDAR}, author = {Pablo Garc{\'\i}a-G{\'o}mez and Noel Rodrigo and Jordi Riu and Josep R Casas and S. Royo} } @conference {cGirbau21, title = {Multiple Object Tracking with Mixture Density Networks for Trajectory Estimation}, booktitle = {CVPR 2021 Robust Video Scene Understanding: Tracking and Video Segmentation (RVSU) Workshop}, year = {2021}, abstract = {

Multiple object tracking faces several challenges that may be alleviated with trajectory information. Knowing the posterior locations of an object helps disambiguating and solving situations such as occlusions, re-identification, and identity switching. In this work, we show that trajectory estimation can become a key factor for tracking, and present TrajE, a trajectory estimator based on recurrent mixture density networks, as a generic module that can be added to existing object trackers. To provide several trajectory hypotheses, our method uses beam search. Also, relying on the same estimated trajectory, we propose to reconstruct a track after an occlusion occurs. We integrate TrajE into two state of the art tracking algorithms, CenterTrack [63] and Tracktor [3]. Their respective performances in the MOTChallenge 2017 test set are boosted 6.3 and 0.3 points in MOTA score, and 1.8 and 3.1 in IDF1, setting a new state of the art for the CenterTrack+TrajE configuration.

}, url = {https://arxiv.org/abs/2106.10950}, author = {Girbau, A. and Xavier Gir{\'o}-i-Nieto and Rius, Ignasi and Marqu{\'e}s, F.} } @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} } @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 {aGene-Mola, title = {Multi-modal Deep Learning for Fuji Apple Detection Using RGB-D Cameras and their Radiometric Capabilities}, journal = {Computers and Electronics in Agriculture}, volume = {162}, year = {2019}, month = {07/2019}, chapter = {689-698}, abstract = {

Fruit detection and localization will be essential for future agronomic management of fruit crops, with applications in yield prediction, yield mapping and automated harvesting. RGB-D cameras are promising sensors for fruit detection given that they provide geometrical information with color data. Some of these sensors work on the principle of time-of-flight (ToF) and, besides color and depth, providethe backscatter signal intensity. However, this radiometric capability has not been exploited for fruit detection applications. This workpresents the KFuji RGB-DS database, composed of 967 multi-modal images containing a total of 12,839 Fuji apples. Compilation of th\ database allowed a study of the usefulness of fusing RGB-D and radiometric information obtained with Kinect v2 for fruit detection. Todo so, the signal intensity was range corrected to overcome signal attenuation, obtaining an image that was proportional to the reflectanceof the scene. A registration between RGB, depth and intensity images was then carried out. The Faster R-CNN model was adapted foruse with five-channel input images: color (RGB), depth (D) and range-corrected intensity signal (S). Results show an improvement of4.46\% in F1-score when adding depth and range-corrected intensity channels, obtaining an F1-score of 0.898 and an AP of 94.8\% whenall channels are used. From our experimental results, it can be concluded that the radiometric capabilities of ToF sensors give valuableinformation for fruit detection.

}, keywords = {Agricultural robotics, Convolutional Neural Networks, Fruit detection, Fruit reflectance, Multi-modal faster R-CNN, RGB-D}, doi = {10.1016/j.compag.2019.05.016}, author = {Gen{\'e}-Mola, Jordi and Ver{\'o}nica Vilaplana and Rosell-Polo, Joan R. and Morros, J.R. and Ruiz-Hidalgo, J. and Gregorio, Eduard} } @mastersthesis {xOriol, title = {Multimodal Hate Speech Detection in Memes}, year = {2019}, abstract = {

This thesis explores a multimodal approach to Hate Speech detection, involving vision and language (text). More specifically, we deal with the context of memes, a form of internet humour which will present additional challenges.\ We first gather meme data from different sources. This way, we create a hate memes dataset for this task. Then, we use this data for the training and evaluation of statistical models, which are based on state-of-the art neural networks.\ We study different ways to fine-tune pretrained descriptors for our specific task. We propose a way to add expert knowledge into the system and orient it into a real world issue-solving system. We also discuss ways to deal with the issue of reduced amount of data, experimenting with a self-supervised learning approach for pre-training.\ We also compare the effect or contribution of each modality in the overall performance of the model.

}, author = {Oriol, Benet}, editor = {Cristian Canton-Ferrer and Xavier Gir{\'o}-i-Nieto} } @article {aVentura, title = {Multiresolution co-clustering for uncalibrated multiview segmentation}, journal = {Signal Processing: Image Communication}, year = {2019}, abstract = {

We propose a technique for coherently co-clustering uncalibrated views of a scene\ with a contour-based representation. Our work extends the previous framework,\ an iterative algorithm for segmenting sequences with small variations, where the\ partition solution space is too restrictive for scenarios where consecutive images\ present larger variations. To deal with a more flexible scenario, we present three\ main contributions. First, motion information has been considered both for\ region adjacency and region similarity. Second, a two-step iterative architecture\ is proposed to increase the partition solution space. Third, a feasible global\ optimization that allows to jointly process all the views has been implemented.\ In addition to the previous contributions, which are based on low-level features,\ we have also considered introducing higher level features as semantic information\ in the co-clustering algorithm. We evaluate these techniques on multiview and\ temporal datasets, showing that they outperform state-of-the-art approaches.

}, keywords = {Co-clustering techniques, Image segmentation, Multiview segmentation, Object segmentation}, doi = {10.1016/j.image.2019.04.010}, url = {https://www.sciencedirect.com/science/article/abs/pii/S0923596518302054}, author = {Ventura, C. and David Varas and Ver{\'o}nica Vilaplana and Xavier Gir{\'o}-i-Nieto and Ferran Marques} } @conference {cRamona, title = {Multi-View 3D Face Reconstruction in the Wild using Siamese Networks}, booktitle = {ICCV 2019 Workshop on 3D Face Alignment in the Wild Challenge Workshop (3DFAW)}, year = {2019}, month = {11/2019}, publisher = {IEEE/CVF}, organization = {IEEE/CVF}, address = {Seoul, South Corea}, abstract = {

In this work, we present a novel learning based approach\ to reconstruct 3D faces from a single or multiple images.\ Our method uses a simple yet powerful architecture based\ on siamese neural networks that helps to extract relevant\ features from each view while keeping the models small. Instead of minimizing multiple objectives, we propose to simultaneously learn the 3D shape and the individual camera\ poses by using a single term loss based on the reprojection\ error, which generalizes from one to multiple views. This allows to globally optimize the whole scene without having to\ tune any hyperparameters and to achieve low reprojection\ errors, which are important for further texture generation.\ Finally, we train our model on a large scale dataset with\ more than 6,000 facial scans. We report competitive results\ in 3DFAW 2019 challenge, showing the effectiveness of our\ method.

}, author = {Ramon, Eduard and Escur, Janna and Xavier Gir{\'o}-i-Nieto} } @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.} } @inbook {bCombalia18, title = {Monte-Carlo Sampling Applied to Multiple Instance Learning for Histological Image Classification}, booktitle = {Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support}, number = {11045}, year = {2018}, pages = {274-281}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, abstract = {

We propose a patch sampling strategy based on a sequential Monte-Carlo method for high resolution image classification in the context of Multiple Instance Learning. When compared with grid sampling and uniform sampling techniques, it achieves higher generalization performance. We validate the strategy on two artificial datasets and two histological datasets for breast cancer and sun exposure classification.

}, isbn = {978-3-030-00889-5}, issn = {10.1007/978-3-030-00889-5}, doi = {10.1007/978-3-030-00889-5}, author = {Marc Combalia and Ver{\'o}nica Vilaplana} } @conference {cCombaliaa, title = {Monte-Carlo Sampling applied to Multiple Instance Learning for Histological Image Classification}, booktitle = {Workshop on Deep Learning in Medical Image Analysis, MICCAI}, year = {2018}, month = {2018}, address = {Granada, Spain}, abstract = {

We propose a patch sampling strategy based on a sequential Monte-Carlo method for high resolution image classification in the context of Multiple Instance Learning. When compared with grid sampling and uniform sampling techniques, it achieves higher generalization performance. We validate the strategy on two artificial datasets and two histological datasets for breast cancer and sun exposure classification.\ 

}, author = {Marc Combalia and Ver{\'o}nica Vilaplana} } @conference {cCombalia, title = {Monte-Carlo Sampling applied to Multiple Instance Learning for Whole Slide Image Classification}, booktitle = {International Conference on Medical Imaging with Deep Learning}, year = {2018}, month = {07/2018}, address = {Amsterdam, The Netherlands}, author = {Marc Combalia and Ver{\'o}nica Vilaplana} } @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} } @unpublished {xFernandezb, title = {Multimodal Knowledge Base Population from News Streams for Media Applications}, year = {2018}, month = {07/2018}, type = {Phd thesis proposal}, abstract = {

Media producers publish large amounts of multimedia content online - both text, audio\ and video. As the online media market grows, the management and delivery of contents\ is becoming a challenge. Semantic and Linking technologies can be used to organize and\ exploit this contents. This dissertation addresses the problem of integrating Semantic Web\ technologies and linking data technologies into Vilynx{\textquoteright}s platform, a system used by media\ producers to manage and explode its contents. For that purpose, Knowledge Graphs (KG)\ and its maintenance through multimodal Knowledge Base Population (KBP) from online\ data extracted from the Web is studied. The Web is a very large unstructured data source\ with millions of text, images, videos and audio. This thesis is willing to generate solutions\ to facilitate automatic learning from these multimodal data and use it in real product applications\ for media.

This thesis is going to be structured in three parts. The first part of the thesis will cover\ the construction of a multimodal KG, which will be the core of the system for knowledge\ extraction, standardization and contextualization.

The\ second part will consist on the construction of the tools that will be used for KBP. For\ that we will construct a multimodal semantic tagging framework, based on the previously\ mentioned KG. This block addresses some typical challenges of KBP and data mining, like:\ name entity recognition (NER), entity linking (EL), context set construction (CSC), structured\ data creation, standardization, entity matching and data fusion.

The third part will focus on the extraction of knowledge from the Web to populate the knowledge\ base. As the KG domain is media, we will populate the KG using events detected from\ news streams using a multilmodal perspective. To detect events we will construct a news\ aggregator system. This part will deal with the problems of Topic Detection and Tracking\ (TDT), Topic Modeling (TM) and multi-document summarization. From these data we will\ learn relations between world entities, that will populate our KG, dealing with the automatic\ detection and update of concepts and relations. Also social media information will be\ analyzed to understand trendiness and world interests.

}, keywords = {Entity Detection, Entity Linking, Knowledge Base Population, Knowledge Graph, Linked Technologies, Multi-document Summarization, multimedia, Multimodal Systems, Natural Language Processing, Semantic Web, Topic Detection and Tracking, Topic Modeling}, author = {Fern{\`a}ndez, D{\`e}lia and Bou-Balust, Elisenda and Xavier Gir{\'o}-i-Nieto} } @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} } @phdthesis {dPerez-Pellitero17, title = {Manifold Learning for Super Resolution}, year = {2017}, school = {Leibniz Universit{\"a}t Hannover}, address = {Hannover}, abstract = {

The development pace of high-resolution displays has been so fast in the recent years that many images acquired with low-end capture devices are already outdated or will be shortly in time. Super Resolution is central to match the resolution of the already existing image content to that of current and future high resolution displays and applications. This dissertation is focused on learning how to upscale images from the statistics of natural images. We build on a sparsity model that uses learned coupled low- and high-resolution dictionaries in order to upscale images.

Firstly, we study how to adaptively build coupled dictionaries so that their content is semantically related with the input image. We do so by using a Bayesian selection stage which finds the best-fitted texture regions from the training dataset for each input image. The resulting adapted subset of patches is compressed into a coupled dictionary via sparse coding techniques.

We then shift from l1 to a more efficient l2 regularization, as introduced by Timofte et al. Instead of using their patch-to-dictionary decomposition, we propose a fully collaborative neighbor embedding approach. In this novel scheme, for each atom in the dictionary we create a densely populated neighborhood from an extensive training set of raw patches (i.e. in the order of hundreds of thousands). This generates more accurate regression functions.

We additionally propose using sublinear search structures such as spherical hashing and trees to speed up the nearest neighbor search involved in regression-based Super Resolution. We study the positive impact of antipodally invariant metrics for linear regression frameworks, and we propose two efficient solutions: (a) the Half Hypersphere Confinement, which enables antipodal invariance within the Euclidean space, and (b) the bimodal tree, whose split functions are designed to be antipodally invariant and which we use in the context of a Bayesian Super Resolution forest.

In our last contribution, we extend antipodal invariance by also taking into consideration the dihedral group of transforms (i.e. rotations and reflections). We study them 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, and we use them to collapse the redundant variability, resulting in a reduced manifold span which, in turn, greatly improves quality performance and reduces the dictionary sizes.

}, author = {E. Perez-Pellitero}, editor = {Rosenhahn, B. and Ruiz-Hidalgo, J.} } @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} } @conference {cFernandez, title = {More cat than cute? Interpretable Prediction of Adjective-Noun Pairs}, booktitle = {ACM Multimedia 2017 Workshop on Multimodal Understanding of Social, Affective and Subjective Attributes}, year = {2017}, month = {10/2017}, publisher = {ACM SIGMM}, organization = {ACM SIGMM}, address = {Mountain View, CA (USA)}, abstract = {

The increasing availability of affect-rich multimedia resources has bolstered interest in understanding sentiment and emotions in and from visual content. Adjective-noun pairs (ANP) are a popular mid-level semantic construct for capturing affect via visually detectable concepts such as {\textquoteleft}{\textquoteleft}cute dog" or {\textquoteleft}{\textquoteleft}beautiful landscape". Current state-of-the-art methods approach ANP prediction by considering each of these compound concepts as individual tokens, ignoring the underlying relationships in ANPs. This work aims at disentangling the contributions of the {\textquoteleft}adjectives{\textquoteright} and {\textquoteleft}nouns{\textquoteright} in the visual prediction of ANPs. Two specialised classifiers, one trained for detecting adjectives and another for nouns, are fused to predict 553 different ANPs. The resulting ANP prediction model is more interpretable as it allows us to study contributions of the adjective and noun components.

}, doi = {10.1145/3132515.3132520}, author = {Fern{\`a}ndez, D{\`e}lia and Woodward, Alejandro and V{\'\i}ctor Campos and Jou, Brendan and Xavier Gir{\'o}-i-Nieto and Chang, Shih-Fu} } @mastersthesis {xCompri, title = {Multi-label Remote Sensing Image Retrieval based on Deep Features}, year = {2017}, abstract = {

Student: Michele Compri

Advisors: Beg{\"u}m Demir (University of Trento) and Xavier Giro-i-Nieto (UPC)

Recent advances in satellite technology has led to an increased volume of remote sensing (RS) image archives, from which retrieving useful information is challenging. Thus, one important research area in remote sensing (RS) is the content-based retrieval of RS images (CBIR). The performance of the CBIR systems depends on the capability of the RS image features in modeling the content of the images as well as the considered retrieval algorithm that assesses the similarity among the features. Existing CBIR systems in the RS literature assume that each image is categorized by only a single label in terms of a land-cover class that is associated to the most significant content of the image. However, RS images usually have complex content, i.e., there are usually several regions within each image related to multiple land-cover classes. Thus, available CBIR systems are not capable of accurately characterizing and exploiting the high level semantic content of RS images for retrieval problems.

To overcome these problems and to effectively characterize the high-level semantic content of RS images, we investigate effectiveness of different deep learning architectures in the framework of multi-label remote sensing image retrieval problems. This is achieved based on a two-steps strategy. In the first step, aConvolutional Neural Network (CNN) pre-trained for image classification with the ImageNet dataset is used off-the-shelf as a feature extractor. In particular, three popular architectures are explored: 1) VGG16; 2) Inception V3; and 3) ResNet50. VGG16 is a CNN characterized by 16 convolutional layers of stacked 3x3 filters, with intermediate max pooling layers and 3 fully connected layers at the end. Inception V3 is an improved version of the former GoogleNet, which contains more layers but less parameters, by removing fully connected layers and using a global average pooling from the last convolutional layer. ResNet50 is even deeper thanks to the introduction of residual layers, that allow data to flow by skipping the convolutional blocks. In he second step of our research, we modify these three off-the-shelf models by fine-tunning their parameters with a subset of RS images and their multi-label information. Experiments carried out on an archive of aerial images show that fine-tuning CNN architectures with annotated images with multi-labels significantly improve the retrieval accuracy with respect to the standard CBIR methods. We find that fine-tunning using with a multi-class approach achieves better results than than considering each label as an independent class. Due to the space constraints, the detailed information on each step of the proposed method will be given in the full version of the paper.\ 

[source code on GitHub]

Multi-label Remote Sensing Image Retrieval based on Deep Features from Xavier Giro
}, author = {Compri, Michele}, editor = {Demir, Beg{\"u}m and Xavier Gir{\'o}-i-Nieto} } @article {aPont-Tuset2015, title = {Multiscale Combinatorial Grouping for Image Segmentation and Object Proposal Generation}, journal = { IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)}, volume = {38}, year = {2017}, pages = {128-140}, abstract = {

We propose a unified approach for bottom-up hierarchical image segmentation and object proposal generation for recognition, called Multiscale Combinatorial Grouping (MCG). For this purpose, we first develop a fast normalized cuts algorithm. We then propose a high-performance hierarchical segmenter that makes effective use of multiscale information. Finally, we propose a grouping strategy that combines our multiscale regions into highly-accurate object proposals by exploring efficiently their combinatorial space. We also present Single-scale Combinatorial Grouping (SCG), a faster version of MCG that produces competitive proposals in under five second per image. We conduct an extensive and comprehensive empirical validation on the BSDS500, SegVOC12, SBD, and COCO datasets, showing that MCG produces state-of-the-art contours, hierarchical regions, and object proposals.

}, url = {http://arxiv.org/abs/1503.00848v1}, author = {Jordi Pont-Tuset and Pablo Arbelaez and Jonathan T. Barron and Marqu{\'e}s, F. and Jitendra Malik} } @phdthesis {dMaceira17, title = {Multi-view depth coding based on a region representation combining color and depth information}, year = {2017}, month = {06/2017}, school = {Universitat Polit{\`e}cnica de Catalunya (UPC)}, type = {PhD}, abstract = {

Depth map data is used to supplement the color data in multi-view sequences. As depth maps present distinct characteristics than natural color images, new coding techniques are required to represent their smooth regions and sharp edges. In this thesis, segmentation-based coding techniques are proposed to encode depth maps by exploiting the redundancy between color and depth information. Methods developed combine partitions obtained from color and depth images to find efficient representations. The color image is assumed to be available before the depth map coding process, therefore a color partition can be obtained at the decoder without introducing coding cost.

Two hierarchical image segmentation algorithms are proposed to generate color and depth partitions for coding applications. The color segmentation obtains a super-pixel representation using color information, spatial distribution and shape complexity. The depth segmentation uses a 3D planar model for each region to extract the structure of the scene. Color and depth partitions are combined in depth map coding methods to find the final coding partition.

Different methods for texture representation have been explored in this thesis. Initial approaches used 2D coding methods, while a 3D representation have been proposed to represent depth maps from multiple views with a unique segmentation. This 3D representation is used to segment depth maps in single-view and multi-view configurations. Final coding partitions are obtained with a ratedistortion optimization over a hierarchy of regions. Segmentation-based coding techniques proposed obtain competitive results with HEVC coding standards.

}, url = {http://hdl.handle.net/2117/110439}, author = {Maceira, M.}, editor = {Ruiz-Hidalgo, J. and Morros, J.R.} } @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} } @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.} } @conference {cVaras15, title = {Multiresolution hierarchy co-clustering for semantic segmentation in sequences with small variations}, booktitle = {ICCV - International Conference on Computer Vision}, year = {2015}, month = {12/2015}, abstract = {

This paper presents a co-clustering technique that, given a collection of images and their hierarchies, clusters nodes from these hierarchies to obtain a coherent multiresolution representation of the image collection. We formalize the co-clustering as a Quadratic Semi-Assignment Problem and solve it with a linear programming relaxation approach that makes effective use of information from hierarchies. Initially, we address the problem of generating an optimal, coherent partition per image and, afterwards, we extend this method to a multiresolution framework. Finally, we particularize this framework to an iterative multiresolution video segmentation algorithm in sequences with small variations. We evaluate the algorithm on the Video Occlusion/Object Boundary Detection Dataset, showing that it produces state-of-the-art results in these scenarios.\ 

}, url = {http://arxiv.org/abs/1510.04842}, author = {David Varas and Alfaro, M. and Marqu{\'e}s, F.} } @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 Josep R Casas 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.} } @mastersthesis {xFerrarons-Betrian, title = {Mobile Visual Search at Catchoom}, year = {2014}, abstract = {

Author: Miquel Ferrarons-Betrian

Advisors:\ Xavier Gir{\'o}-i-Nieto\ (UPC) and Tomasz Adamek\ (Catchoom)

Degree: Master in Computer Vision (1 year)

}, keywords = {feature selection, large-scale visual search, Mobile visual search, synthetic views matching, visual word}, author = {Ferrarons-Betrian, Miquel}, editor = {Tomasz Adamek and Xavier Gir{\'o}-i-Nieto} } @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 {cArbelaez14, title = {Multiscale Combinatorial Grouping}, booktitle = {Computer Vision and Pattern Recognition (CVPR)}, year = {2014}, abstract = {

We propose a unified approach for bottom-up hierarchical image segmentation and object candidate generation for recognition, called Multiscale Combinatorial Grouping (MCG). For this purpose, we first develop a fast normalized cuts algorithm. We then propose a high-performance hierarchical segmenter that makes effective use of multiscale information. Finally, we propose a grouping strategy that combines our multiscale regions into highly-accurate object candidates by efficiently exploring their combinatorial space. We conduct extensive experiments on both the BSDS500 and on the PASCAL 2012 segmentation datasets, showing that MCG produces state-of-the-art contours, hierarchical regions, and object candidates.

Code and pre-computed results available here.

}, author = {Pablo Arbelaez and Jordi Pont-Tuset and Barron, Jon and Marqu{\'e}s, F. and Jitendra Malik} } @conference {cGallego14a, title = {Multiview Foreground Segmentation using 3D Probabilistic Model}, booktitle = {ICIP, IEEE International Conference on Image Processing}, year = {2014}, month = {10/2014}, abstract = {

We propose a complete multi-view foreground segmentation and 3D reconstruction system that defines a 3-dimensional probabilistic model to model the foreground object in the 3 spatial dimensions, thus gathering the information from all the camera views. This 3D model is projected to each one of the views in order to perform the 2D segmentation with the foreground information shared by all the cameras. Then, for each one of the views, a MAP-MRF classification framework is applied between the projected region-based foreground model, the pixel-wise background model and the regionbased shadow model defined for each view. The resultant masks are used to compute the next 3-dimensional reconstruction. This system achieves correct results by reducing the false positive and false negative errors in sequences where some camera sensors can present camouflage situations between foreground and background. Moreover, the use of the 3D model opens possibilities to use it for objects recognition or human activity understanding.

}, author = {Gallego, J. and M. Pard{\`a}s} } @conference {cPont-Tuset13, title = {Measures and Meta-Measures for the Supervised Evaluation of Image Segmentation}, booktitle = {Computer Vision and Pattern Recognition (CVPR)}, year = {2013}, month = {06/2013}, abstract = {

This paper tackles the supervised evaluation of image segmentation algorithms. First, it surveys and structures the measures used to compare the segmentation results with a ground truth database; and proposes a new measure: the precision-recall for objects and parts. To compare the goodness of these measures, it defines three quantitative meta-measures involving six state of the art segmentation methods. The meta-measures consist in assuming some plausible hypotheses about the results and assessing how well each measure reflects these hypotheses. As a conclusion, this paper proposes the precision-recall curves for boundaries and for objects-and-parts as the tool of choice for the supervised evaluation of image segmentation. We make the datasets and code of all the measures publicly available.

Examples of the meta-measure principles: How good are\ the evaluation measures at distinguishing these pairs of partitions?

}, author = {Jordi Pont-Tuset and Marqu{\'e}s, F.} } @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 Josep R Casas} } @conference {cLopez-Mendez12, title = {Metric Learning from Poses for Temporal Clustering of Human Motion}, booktitle = {British Machine Vision Conference 2012}, year = {2012}, month = {09/2012}, address = {Guildford, UK}, abstract = {

Temporal clustering of human motion into semantically meaningful behaviors is a challenging task. While unsupervised methods do well to some extent, the obtained clusters often lack a semantic interpretation. In this paper, we propose to learn what makes a sequence of human poses different from others such that it should be annotated as an action. To this end, we formulate the problem as weakly supervised temporal clustering for an unknown number of clusters. Weak supervision is attained by learning a metric from the implicit semantic distances derived from already annotated databases. Such a metric contains some low-level semantic information that can be used to effectively segment a human motion sequence into distinct actions or behaviors. The main advantage of our approach is that metrics can be successfully used across datasets, making our method a compelling alternative to unsupervised methods. Experiments on publicly available mocap datasets show the effectiveness of our approach.

}, doi = {10.5244/C.26.49}, author = {L{\'o}pez-M{\'e}ndez, A. and Gall, J. and Josep R Casas and van Gool, L.} } @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} } @article {aLopez-Mendez12, title = {Model-Based Recognition of Human Actions by Trajectory Matching in Phase Spaces}, journal = {Image and Vision Computing}, year = {2012}, abstract = {

This paper presents a human action recognition framework based on the theory of nonlinear dynamical systems. The ultimate aim of our method is to recognize actions from multi-view video. We estimate and represent human motion by means of a virtual skeleton model providing the basis for a view-invariant representation of human actions. Actions are modeled as a set of weighted dynamical systems associated to different model variables. We use time-delay embeddings on the time series resulting of the evolution of model variables along time to reconstruct phase portraits of appropriate dimensions. These phase portraits characterize the underlying dynamical systems. We propose a distance to compare trajectories within the reconstructed phase portraits. These distances are used to train SVM models for action recognition. Additionally, we propose an efficient method to learn a set of weights reflecting the discriminative power of a given model variable in a given action class. Our approach presents a good behavior on noisy data, even in cases where action sequences last just for a few frames. Experiments with marker-based and markerless motion capture data show the effectiveness of the proposed method. To the best of our knowledge, this contribution is the first to apply time-delay embeddings on data obtained from multi-view video.

}, keywords = {action recognition}, issn = {0262-8856}, doi = {10.1016/j.imavis.2012.06.007}, url = {http://www.sciencedirect.com/science/article/pii/S0262885612000959?v=s5}, author = {L{\'o}pez-M{\'e}ndez, A. and Josep R Casas} } @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 {cGiro-i-Nieto12b, title = {Multiscale annotation of still images with GAT}, booktitle = {Proceedings of the 1st International Workshop on Visual Interfaces for Ground Truth Collection in Computer Vision Applications}, year = {2012}, publisher = {ACM}, organization = {ACM}, address = {Capri, Italy}, abstract = {

This paper presents GAT, a Graphical Annotation Tool for still images that works both at the global and local scales. This interface has been designed to assist users in the an- notation of images with relation to the semantic classes de- scribed in an ontology. Positive, negative and neutral labels can be assigned to both the whole images or parts of them. The user interface is capable of exploiting segmentation data to assist in the selection of objects. Moreover, the annota- tion capabilities are complemented with additional function- alities that allow the creation and evaluation of an image classifier. The implemented Java source code is published under a free software license.\ 

}, keywords = {annotation, image, interactive, segmentation, semantics}, isbn = {978-1-4503-1405-3}, doi = {10.1145/2304496.2304497}, url = {http://doi.acm.org/10.1145/2304496.2304497}, author = {Xavier Gir{\'o}-i-Nieto and Martos, Manel} } @article {aCalderero12, title = {Multispectral Cooperative Partition Sequence Fusion for Joint Classification and Hierarchical Segmentation}, journal = {Geoscience and Remote Sensing Letters, IEEE}, volume = {9}, year = {2012}, pages = {1012-1016}, abstract = {

In this letter, a region-based fusion methodology is presented for joint classification and hierarchical segmentation of specific ground cover classes from high-spatial-resolution remote sensing images. Multispectral information is fused at the partition level using nonlinear techniques, which allows the different relevance of the various bands to be fully exploited. A hierarchical segmentation is performed for each individual band, and the ensuing segmentation results are fused in an iterative and cooperative way. At each iteration, a consensus partition is obtained based on information theory and is combined with a specific ground cover classification. Here, the proposed approach is applied to the extraction and segmentation of vegetation areas. The result is a hierarchy of partitions with the most relevant information of the vegetation areas at different levels of resolution. This system has been tested for vegetation analysis in high-spatial-resolution images from the QuickBird and GeoEye satellites.

}, keywords = {GeoEye satellite, geophysical image processing, geophysical techniques, ground cover classification, hierarchical segmentation, high-spatial-resolution remote sensing images, image classification, image fusion, image region analysis, Image segmentation, information fusion, information theory, joint classification, Joints, Merging, multispectral cooperative partition sequence fusion, multispectral images, multispectral information, nonlinear techniques, partition level, QuickBird satellite, region merging, region-based fusion methodology, Remote sensing, Spatial resolution, specific ground cover classes, Vegetation mapping}, issn = {1545-598X}, doi = {10.1109/LGRS.2012.2188776}, author = {Calderero, F. and F. Eugenio and Marcello, J. and Marqu{\'e}s, F.} } @inbook {bNavarro12, title = {Multi-view Body Tracking with a Detector-Driven Hierarchical Particle Filter}, booktitle = {Lecture Notes in Computer Science: Articulated Motion and Deformable Objects}, series = {Lecture Notes in Computer Science}, volume = {7378}, year = {2012}, pages = {82-91}, publisher = {Springer }, organization = {Springer }, address = {Berlin / Heidelberg}, abstract = {

In this paper we present a novel approach to markerless human motion capture that robustly integrates body part detections in multiple views. The proposed method fuses cues from multiple views to enhance the propagation and observation model of particle filtering methods aiming at human motion capture. We particularize our method to improve arm tracking in the publicly available IXMAS dataset. Our experiments show that the proposed method outperforms other state-of-the-art approaches.

}, isbn = {978-3-642-31566-4}, doi = {10.1007/978-3-642-31567-1_8}, author = {Navarro, Sergio and L{\'o}pez-M{\'e}ndez, A. and Alcoverro, M. and Josep R Casas}, editor = {Perales, Francisco and Fisher, Robert and Moeslund, Thomas} } @conference {cNavarro12 , title = {Multi-view Body Tracking with a Detector-Driven Hierarchical Particle Filter}, booktitle = {7th International Conference AMDO 2012}, year = {2012}, month = {07/2012}, publisher = {Springer}, organization = {Springer}, address = {Port d{\textquoteright}Andratx, Mallorca}, abstract = {

In this paper we present a novel approach to markerless human motion capture that robustly integrates body part detections in multiple views. The proposed method fuses cues from multiple views to enhance the propagation and observation model of particle filtering methods aiming at human motion capture. We particularize our method to improve arm tracking in the publicly available IXMAS dataset. Our experiments show that the proposed method outperforms other state-of-the-art approaches.

}, doi = {10.1007/978-3-642-31567-1_8}, author = {Navarro, Sergio and L{\'o}pez-M{\'e}ndez, A. and Alcoverro, M. and Josep R Casas} } @article {aRuiz-Hidalgo12, title = {Multiview depth coding based on combined color/depth segmentation}, journal = {Journal of visual communication and image representation}, volume = {23}, number = {1}, year = {2012}, pages = {42{\textendash}52}, abstract = {

In this paper a new coding method for multiview depth video is presented. Considering the smooth structure and sharp edges of depth maps, a segmentation based approach is proposed. This allows further preserving the depth contours thus introducing fewer artifacts in the depth perception of the video. To reduce the cost associated with partition coding, an estimation of the depth partition is built using the decoded color view segmentation. This estimation is refined by sending some complementary information about the relevant differences between color and depth partitions. For coding the depth content of each region, a decomposition into orthogonal basis is used in this paper although similar decompositions may be also employed. Experimental results show that the proposed segmentation based depth coding method outperforms H.264/AVC and H.264/MVC by more than 2dB at similar bitrates.

}, keywords = {3DTV, Depth map, multiview video coding, virtual view}, issn = {1047-3203}, doi = {10.1016/j.jvcir.2011.08.001}, url = {http://www.sciencedirect.com/science/article/pii/S1047320311001040}, author = {Ruiz-Hidalgo, J. and Morros, J.R. and Aflaki, P. and Calderero, F. and Marqu{\'e}s, F.} } @phdthesis {dObrador11, title = {Media Aesthetics Based Multimedia Storytelling}, year = {2011}, school = {Universitat Polit{\`e}cnica de Catalunya (UPC)}, type = {phd}, abstract = {

Since the earliest of times, humans have been interested in recording their life experiences, for future reference and for storytelling purposes. This task of recording experiences {\textendash}i.e., both image and video capture{\textendash} has never before in history been as easy as it is today. This is creating a digital information overload that is becoming a great concern for the people that are trying to preserve their life experiences. As high-resolution digital still and video cameras become increasingly pervasive, unprecedented amounts of multimedia, are being downloaded to personal hard drives, and also uploaded to online social networks on a daily basis. The work presented in this dissertation is a contribution in the area of multimedia organization, as well as automatic selection of media for storytelling purposes, which eases the human task of summarizing a collection of images or videos in order to be shared with other people. As opposed to some prior art in this area, we have taken an approach in which neither user generated tags nor comments {\textendash}that describe the photographs, either in their local or on-line repositories{\textendash} are taken into account, and also no user interaction with the algorithms is expected. We take an image analysis approach where both the context images {\textendash}e.g. images from online social networks to which the image stories are going to be uploaded{\textendash}, and the collection images {\textendash}i.e., the collection of images or videos that needs to be summarized into a story{\textendash}, are analyzed using image processing algorithms. This allows us to extract relevant metadata that can be used in the summarization process. Multimedia-storytellers usually follow three main steps when preparing their stories: first they choose the main story characters, the main events to describe, and finally from these media sub-groups, they choose the media based on their relevance to the story as well as based on their aesthetic value. Therefore, one of the main contributions of our work has been the design of computational models {\textendash}both regression based, as well as classification based{\textendash} that correlate well with human perception of the aesthetic value of images and videos. These computational aesthetics models have been integrated into automatic selection algorithms for multimedia storytelling, which are another important contribution of our work. A human centric approach has been used in all experiments where it was feasible, and also in order to assess the final summarization results, i.e., humans are always the final judges of our algorithms, either by inspecting the aesthetic quality of the media, or by inspecting the final story generated by our algorithms. We are aware that a perfect automatically generated story summary is very hard to obtain, given the many subjective factors that play a role in such a creative process; rather, the presented approach should be seen as a first step in the storytelling creative process which removes some of the ground work that would be tedious and time consuming for the user. Overall, the main contributions of this work can be capitalized in three: (1) new media aesthetics models for both images and videos that correlate with human perception, (2) new scalable multimedia collection structures that ease the process of media summarization, and finally, (3) new media selection algorithms that are optimized for multimedia storytelling purposes

}, url = {http://hdl.handle.net/10803/33293}, author = {Obrador, P.}, editor = {Josep R Casas} } @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.} } @article {aCanton-Ferrer11a, title = {Multi-camera multi-object voxel-based Monte Carlo 3D tracking strategies}, journal = {Eurasip journal on advances in signal processing}, volume = {2011}, number = {114}, year = {2011}, pages = {1{\textendash}15}, abstract = {

This article presents a new approach to the problem of simultaneous tracking of several people in low-resolution sequences from multiple calibrated cameras. Redundancy among cameras is exploited to generate a discrete 3D colored representation of the scene, being the starting point of the processing chain. We review how the initiation and termination of tracks influences the overall tracker performance, and present a Bayesian approach to efficiently create and destroy tracks. Two Monte Carlo-based schemes adapted to the incoming 3D discrete data are introduced. First, a particle filtering technique is proposed relying on a volume likelihood function taking into account both occupancy and color information. Sparse sampling is presented as an alternative based on a sampling of the surface voxels in order to estimate the centroid of the tracked people. In this case, the likelihood function is based on local neighborhoods computations thus dramatically decreasing the computational load of the algorithm. A discrete 3D re-sampling procedure is introduced to drive these samples along time. Multiple targets are tracked by means of multiple filters, and interaction among them is modeled through a 3D blocking scheme. Tests over CLEAR-annotated database yield quantitative results showing the effectiveness of the proposed algorithms in indoor scenarios, and a fair comparison with other state-of-the-art algorithms is presented. We also consider the real-time performance of the proposed algorithm.\ 

}, issn = {1687-6172}, doi = {10.1186/1687-6180-2011-114}, url = {http://asp.eurasipjournals.com/content/2011/1/114}, author = {Cristian Canton-Ferrer and Josep R Casas and M. Pard{\`a}s and Monte, E.} } @article {aCanton-Ferrer10, title = {Marker-based human motion capture in multi-view sequences}, journal = {Eurasip journal on advances in signal processing}, volume = {2010}, number = {Article ID 105476}, year = {2010}, pages = {1{\textendash}11}, abstract = {

This paper presents a low-cost real-time alternative to available commercial human motion capture systems. First, a set of distinguishable markers are placed on several human body landmarks, and the scene is captured by a number of calibrated and synchronized cameras. In order to establish a physical relation among markers, a human body model is defined. Markers are detected on all camera views and delivered as the input of an annealed particle filter scheme where every particle encodes an instance of the pose of the body model to be estimated. Likelihood between particles and input data is performed through the robust generalized symmetric epipolar distance and kinematic constrains are enforced in the propagation step towards avoiding impossible poses. Tests over the HumanEva annotated data set yield quantitative results showing the effectiveness of the proposed algorithm. Results over sequences involving fast and complex motions are also presented.

}, keywords = {CHIL, PROVEC}, issn = {1687-6172}, doi = {10.1155/2010/105476}, url = {http://www.hindawi.com/journals/asp/2010/105476.html}, author = {Cristian Canton-Ferrer and Josep R Casas and M. Pard{\`a}s} } @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 {cOliveras09, title = {Maximum likelihood factor analysis in malaria cytokines analysis and modelling}, booktitle = {IEEE International Workshop on Genomic Signal Processing and Statistics}, year = {2009}, isbn = {84-605-9799-7}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=5174320\&arnumber=5174336\&count=57\&index=14}, author = {Albert Oliveras} } @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 Josep R Casas} } @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.} } @book {eMarques09, title = {Multimodal signal processing: theory and applications for human-computer interaction}, year = {2009}, isbn = {9780123748256}, editor = {Marqu{\'e}s, F.} } @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 Josep R Casas and Ruiz-Hidalgo, J.} } @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 {aMarcello08, title = {Motion estimation techniques to automatically track oceanographic thermal structures in multi-sensor image sequences}, journal = {IEEE transactions on geoscience and remote sensing}, volume = {46}, number = {9}, year = {2008}, pages = {2743{\textendash}2762}, issn = {0196-2892}, author = {Marcello, J. and F. Eugenio and Marqu{\'e}s, F. and Hernandez-Guerra, A. and Gasull, A.} } @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 Josep R Casas 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 Josep R Casas and M. Pard{\`a}s} } @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 Josep R Casas and Hernando, J.} } @conference {cLopez-Mendez07, title = {Multi-person 3D Tracking with Particle Filters on Voxels}, booktitle = {2007 International Conference on Acoustics, Speech and Signal Processing}, year = {2007}, abstract = {

This paper presents a new approach 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 scene. 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. Test over annotated databases yield quantitative results showing the effectiveness of the proposed algorithm in the indoor scenarios.

}, author = {L{\'o}pez-M{\'e}ndez, A. and Cristian Canton-Ferrer and Josep R Casas} } @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 Josep R Casas and M. Pard{\`a}s} } @conference {cCalderero07, title = {Multiple view region matching using as a Lagrangian optimization problem}, booktitle = {2007 International Conference on Acoustics, Speech and Signal Processing}, year = {2007}, author = {Calderero, F. and Marqu{\'e}s, F. and Ortega, A.} } @conference {cNeumann06, title = {Multimodal Integration of Sensor Network}, booktitle = {Proceedings of 3rd IFIP Conference on Artificial Intelligence Applications \& Innovations}, year = {2006}, month = {09/2006}, publisher = {Springer}, organization = {Springer}, address = {Athens, Greece}, isbn = {978-0-387-34223}, author = {Neumann, J. and Josep R Casas and Macho, D. and Ruiz-Hidalgo, J.} } @inbook {bNeumann06, title = {Multimodal Integration of Sensor Network}, booktitle = {Artificial Intelligence Applications and Innovations}, volume = {204}, year = {2006}, pages = {312{\textendash}323}, publisher = {Springer}, organization = {Springer}, address = {Boston}, abstract = {

At the Universitat Polit{\`e}cnica de Catalunya (UPC), a Smart Room has been equipped with 85 microphones and 8 cameras. This paper describes the setup of the sensors, gives an overview of the underlying hardware and software infrastructure and indicates possibilities for high- and low-level multi-modal interaction. An example of usage of the information collected from the distributed sensor network is explained in detail: the system supports a group of students that have to solve a lab assignment related problem.

}, isbn = {978-0-387-34223-8}, doi = {10.1007/0-387-34224-9_36}, author = {Neumann, J. and Josep R Casas and Macho, D. and Ruiz-Hidalgo, J.} } @conference {cLuque06, title = {Multimodal Person Identification in a Smart Room}, booktitle = {IV Jornadas en Tecnolog{\'\i}a del Habla}, year = {2006}, pages = {327{\textendash}331}, isbn = {84-96214-82-6}, author = {Luque, J. and Morros, J.R. and Anguita, J. and Farr{\'u}s, M. and Macho, D. and Marqu{\'e}s, F. and Mart{\'\i}nez, C. and Ver{\'o}nica Vilaplana and Hernando, J.} } @conference {cChang05, title = {A Motion-based Binary Partition Tree approach to Video Object Segmentation}, booktitle = {IEEE International Conference on Image Processing}, year = {2005}, pages = {430{\textendash}433}, isbn = {0-7803-9135-7}, author = {Chang, C. and M. Pard{\`a}s and Marqu{\'e}s, F.} } @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} } @article {aCasas05, title = {Mutual feedback scheme for face detection and tracking aimed at density estimation in demonstrations}, journal = {IEE Proceedings-Vision, Image and Signal Processing}, volume = {152}, number = {3}, year = {2005}, month = {05/2005}, pages = {334{\textendash}346}, abstract = {

Crowded video sequences, like those of demonstrations, offer an interesting challenge for object detection and tracking owing to their complexity: taken outdoors, often in different illumination conditions; showing faces not in frontal view, with perspective effects, complex background, etc. Tracking of individuals becomes a difficult task due to the high number of occlusions. The paper proposes a mutual feedback spatiotemporal detection strategy to tackle these problems. The system improves its efficiency thanks to a cooperative approach between spatial detection and temporal tracking. Spatial detection is based on skin colour classification and shape analysis by morphological tools. Temporal tracking is based on the analysis of the optical flow. The mutual feedback scheme benefits both spatial detection and temporal tracking. In order to deal with multiple occlusions, a graph-based tracking technique, which takes advantage of neighbourhood consistency, has been introduced.

}, issn = {1350-245X}, doi = {10.1049/ip-vis:20045071}, url = {http://dx.doi.org/10.1049/ip-vis:20045071}, author = {Josep R Casas and Puig-Sitjes, A. and Puig-Folch, P.} } @conference {cGiro-i-Nieto04, title = {The Moonlight project: bringing light to our satellite}, booktitle = {Proceedings of the 4th International Conference on Solar Power from Space SPS{\textquoteright}04 The 4th International Conference on Solar Power SPS{\textquoteright}04 together with the 5th International Conference on Wireless Power transmissions WPT 5}, year = {2004}, pages = {99{\textendash}100}, isbn = {92-9092-878-6}, author = {Xavier Gir{\'o}-i-Nieto and Aragon, M. and Prats, X. and Acero, L.} } @conference {cEugenio03, title = {Marine coastal dynamic study using an automatic structure detection and spatial registration tool}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium (IGARSS-03)}, year = {2003}, pages = {1{\textendash}3}, isbn = {0-7803-7930-6}, author = {F. Eugenio and Marcello, J. and Marqu{\'e}s, F.} } @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 {c03, title = {The Moon Orbital Mirror}, booktitle = {54th International Astronautical Congress (IAC)}, year = {2003}, month = {10/2003}, address = {Bremen, Germany}, abstract = {

The current state of space exploration pushes that one of the next steps is the establishment of a permanent base on the Moon. This paper describes the problems related to lunar night, explains the benefits that the Moon Orbital Mirror would offer and gives a possible design for the satellite.

}, url = {http://www.zarm.uni-bremen.de/iaf2003/abstracts/data/pdf/IAC-03-IAA.1.1.02.PDF}, author = {Acero, LLu{\'\i}s and {\`A}. Arag{\'o}n and Xavier Gir{\'o}-i-Nieto and Prats, Xavier} } @conference {cGiro-i-Nieto02, title = {MPEG-7 Descriptors for Earth Observation Satellites}, booktitle = {International Astronautical Congress}, year = {2002}, month = {09/2002}, pages = {1{\textendash}4}, publisher = {Inernational Astronautical Federation}, organization = {Inernational Astronautical Federation}, address = {Houston, Texas (USA)}, abstract = {

The amount of digital multimedia information has experienced a spectacular growth during the last years thanks to the advances on digital systems of image, video and audio acquisition. As a response to the need of organizing all this information, ISO/IEC has developed a new standard for multimedia content description called MPEG-7. Among other topics, MPEG-7 defines a set of multimedia descriptors that can be automatically generated using signal processing techniques. Earth Observation Satellites generate large quantities of images stored on enormous databases that can take advantage of the new standard. An automatic indexation of these images using MPEG-7 meta-data can improve their contents management as well as simplify interaction between independent databases. This paper gives an overall description on MPEG-7 standard focusing on the low-level Visual Descriptors. These descriptors can be grouped into four categories: color, texture, shape and motion. Visual Color Descriptors represent the color distribution of an image in terms of a specified color space. Visual Texture Descriptors define the visual pattern of an image according to its homogeneities and non-homogeneities. Visual Shape Descriptors describe the shape of 2D and 3D objects being, at the same time, invariant to scaling, rotation and translation. Motion Descriptors give the essential characteristics of objects and camera motions.

These descriptors can be used individually or in combination to index and retrieve satellite images of the Earth from a database. For example, oceans and glaciers can be discerned based on their Color Descriptors, also cities and desert based on the Texture Descriptors, island images can be grouped using the Shape descriptors and cyclone trajectories studied and compared using Motion Descriptors.

}, author = {Xavier Gir{\'o}-i-Nieto and Marqu{\'e}s, F. and Marcello, J. and F. Eugenio} } @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 {cMarques00, title = {A morphological approach for segmentation and tracking of human faces}, booktitle = {International Symposium on Image/Video Communications over Fixed and Mobile Networks}, year = {2000}, pages = {38{\textendash}43}, author = {Marqu{\'e}s, F. and Ver{\'o}nica Vilaplana} } @conference {cMarques00a, title = {A morphological approach for segmentation and tracking of human faces}, booktitle = {15th IAPR International Conference on Pattern Recognition}, year = {2000}, isbn = {0-7695-0750-6}, author = {Marqu{\'e}s, F. and Ver{\'o}nica Vilaplana} } @conference {cMarques99, title = {A morphological approach for human face segmentation and tracking}, booktitle = {Workshop on Image Analysis for Multimedia Services}, year = {1999}, pages = {41{\textendash}44}, author = {Marqu{\'e}s, F. and Ver{\'o}nica Vilaplana and Buxes, A.} } @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 {cCasas96b, title = {Morphological Interpolation for Image Coding}, booktitle = {ICAOS {\textquoteright}96: 12th International Conference on Analysis and Optimization of Systems Images, Wavelets and PDEs }, year = {1996}, month = {06/1996}, pages = {295{\textendash}304}, address = {Paris}, author = {Josep R Casas} } @inbook {bCasas96, title = {Morphological Interpolation for Image Coding}, booktitle = {Images, Wavelets and PDEs}, volume = {219}, number = {Lecture Notes in Control and Information Sciences}, year = {1996}, pages = {295{\textendash}304}, publisher = {Springer}, organization = {Springer}, address = {Berlin / Heidelberg}, abstract = {

The aim of this paper is to present a new interpolation technique intended for spatial interpolation from sparse data sets. The proposed implementation, which is based on non-linear morphological operators, overperforms linear interpolation by means of diffusion processes performing iterative space-variant filtering on the initial image. Morphological interpolation is applied to sketch-based image coding. We put forward a perceptually motivated two-component image model that strongly relies on morphological operators. The watershed is used to detect strong edge features in the first component of the model. The smooth areas of the image are recovered from the extracted edge information by morphological interpolation. The residual component, containing fine textures, is separately coded by a subband coding scheme.

}, isbn = {978-3-540-76076-4}, doi = {10.1007/3-540-76076-8_142}, author = {Josep R Casas} } @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 Josep R Casas 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} } @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 = {Josep R Casas and Salembier, P. and Torres, L.} } @conference {cCasas94b, title = {Morphological filter for lossless image subsampling}, booktitle = {IEEE International Conference on Image Processing{\textquoteright}94}, year = {1994}, pages = {903{\textendash}907}, isbn = {0-8186-6950-0}, author = {Josep R Casas and Torres, L.} } @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.} } @conference {cCasas94d, title = {Morphological scheme for morphometric analysis of epidermal biopsy images}, booktitle = {International Symposium on Mathematical Morphology and its Applications to Image Processing II}, year = {1994}, address = {Fontainebleau}, 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 {\textquoteleft}a priori{\textquoteright} model of the images. The watershed algorithm has proven to be
a very powerful tool for the introduction of such {\textquoteleft}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.

}, isbn = {0-7923-3093-5}, author = {Josep R Casas and Esteban, P. and Moreno, A. and Carrera, M.} } @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 = {Josep R Casas 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.} } @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 {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.} } @phdthesis {dMarques92, title = {Multiresolution image segmentation based on camporend random fields: Application to image coding}, year = {1992}, school = {Universitat Polit{\`e}cnica de Catalunya (UPC)}, type = {phd}, url = {http://hdl.handle.net/10803/6910}, author = {Marqu{\'e}s, F.}, editor = {Gasull, A.} }