@conference {cLozano23, title = {Optical Phased Array Antenna Apodization for Lidar in Autonomous Vehicles}, booktitle = {XIII Reuni{\'o}n OptoElectr{\'o}nica}, year = {2023}, month = {06/2023}, publisher = {OPTOEL}, organization = {OPTOEL}, address = {Sevilla, Spain}, abstract = {

This paper presents the specific design of an Optical Phased Array antenna (OPA) to apodize the emission of a lidar in the context of a project where diverse optoelectronic sensors such as cameras, radars, and commercial lidars are used to provide data in order to fuse them and develop perception for robots as future autonomous vehicles. While mechanical based lidars are already commercially available, this work focuses on designing much more robust and potentially cheaper lidars based on photonic integrated circuits and energy optimization through the apodization of the emission of the OPA.

}, url = {https://www.optoel2023.es/94299/section/44205/optoel-2023.html}, author = {Jos{\'e} Lozano and Humberto Jim{\'e}nez and Sergio Torres and Pau Biosca and Bernat Fontanet and Jorge Pinazo and Adolfo Ler{\'\i}n and Federico Dios and Casas, J. and Jos{\'e} Antonio L{\'a}zaro} } @article {xGiro-i-Nieto21a, title = {Object Detection with Deep Learning}, year = {2021}, abstract = {

Object detection in computer vision is the task of localizing and categorizing object instances in still images. This talk reviews the main approaches for solving the task with deep neural networks, following a historically perspective starting from the image classification task.


[GSlides]

}, author = {Xavier Gir{\'o}-i-Nieto and Ventura, C.} } @article {xEscobar21, title = {Object Model Adaptation for Multiple Object Tracking}, year = {2021}, abstract = {

Multiple object tracking is a broadly used task in multi- ple applications, all the way from bioengineering to security applications. In this paper we propose a variation of RVOS by adding the center estimation of detected instances, by means of a second head in the decoder which is assigned the task of detecting the corresponding object{\textquoteright}s bounding box arithmetic center. We have trained the model using three variants of the cross-entropy loss, which has been adapted to tackle the class imbalance caused by the fact that the center of an object is represented by only one pixel of the image, and have obtained some promising results.

}, author = {Escobar, Miquel}, editor = {Girbau, A. and Ventura, C. and Xavier Gir{\'o}-i-Nieto and Marqu{\'e}s, F.} } @conference {cGiro-i-Nieto, title = {One Perceptron to Rule Them All: Language, Vision, Audio and Speech (tutorial)}, booktitle = {ACM International Conference on Multimedia Retrieval (ICMR) 2020}, year = {2020}, month = {06/2020}, publisher = {ACM}, organization = {ACM}, address = {Dublin, Ireland}, abstract = {

Deep neural networks have boosted the convergence of multimedia data analytics in a unified framework shared by practitioners in natural language, vision and speech. Image captioning, lip reading or video sonorization are some of the first applications of a new and exciting field of research exploiting the generalization properties of deep neural representation. This tutorial will firstly review the basic neural architectures to encode and decode vision, text and audio, to later review the those models that have successfully translated information across modalities.

Part II: Neural Encoders \& Decoders [GSlides] [Video]

Part III: Language \& Vision: [GSlides] [Video]

Part IV: Audio \& Vision: [GSlides] [Video]

Part V: Speech \& Vision [GSlides]
}, keywords = {deep learning; multimodal; cross-modal; joint embeddings}, doi = {https://doi.org/10.1145/3372278.3390740}, author = {Xavier Gir{\'o}-i-Nieto} } @article {xGiro-i-Nieto19a, title = {One Perceptron to Rule Them All: Language and Vision}, year = {2019}, abstract = {

Deep neural networks have boosted the convergence of multimedia data analytics in a unified framework shared by practitioners in natural language and vision. Image captioning, visual question answering or multimodal translation are some of the first applications of a new and exciting field that exploiting the generalization properties of deep neural representations. This talk will provide an overview of how vision and language problems are addressed with deep neural networks, and the exciting challenges being addressed nowadays by the research community.

One Perceptron to Rule Them All: Language and Vision from Universitat Polit{\`e}cnica de Catalunya
}, author = {Xavier Gir{\'o}-i-Nieto} } @conference {cLin19, title = {One Shot Learning for Generic Instance Segmentation in RGBD Videos}, booktitle = {International Conference on Computer Vision, Theory and Applications}, year = {2019}, month = {02/2019}, publisher = {SciTePress}, organization = {SciTePress}, address = {Prague}, abstract = {

Hand-crafted features employed in classical generic instance segmentation methods have limited discriminative power to distinguish different objects in the scene, while Convolutional Neural Networks (CNNs) based semantic segmentation is restricted to predefined semantics and not aware of object instances. In this paper, we combine the advantages of the two methodologies and apply the combined approach to solve a generic instance segmentation problem in RGBD video sequences. In practice, a classical generic instance segmentation method is employed to initially detect object instances and build temporal correspondences, whereas instance models are trained based on the few detected instance samples via CNNs to generate robust features for instance segmentation. We exploit the idea of one shot learning to deal with the small training sample size problem when training CNNs. Experiment results illustrate the promising performance of the proposed approach.

}, keywords = {Convolutional Neural Network, Instance Segmentation, One Shot Learning}, isbn = {978-989-758-354-4}, doi = {10.5220/0007259902330239}, author = {X. Lin and Casas, J. and M. Pard{\`a}s} } @article {xGiro-i-Nieto18a, title = {One Perceptron to Rule them All}, year = {2018}, abstract = {
Once Perceptron to Rule Them all: Deep Learning for Multimedia from Universitat Polit{\`e}cnica de Catalunya
}, author = {Xavier Gir{\'o}-i-Nieto} } @conference {cShou, title = {Online Action Detection in Untrimmed, Streaming Videos}, booktitle = {European Conference on Computer Vision (ECCV)}, year = {2018}, month = {02/2018}, address = {Munich, German}, abstract = {

}, url = {https://arxiv.org/abs/1802.06822}, author = {Shou, Zheng and Pan, Junting and Chan, Johnatan and Miyazawa, Kazuyuki and Mansour, Hassan and Vetro, Anthony and Xavier Gir{\'o}-i-Nieto and Chang, Shih-Fu} } @conference {cLopez-Palma, title = {Oriented trajectories as a method for audience measurement}, booktitle = {27th International Symposium on Industrial Electronics (ISIE)}, year = {2018}, month = {06/2018}, publisher = {IEEE}, organization = {IEEE}, address = {Cairns, Australia}, abstract = {

The quantification of the attention received by advertisements is of paramount importance to determine its effectiveness. In this work, a simple and effective objective method for the assessment of the attention given to advertisements is provided. The proposed method is based on computing the oriented trajectory of the different test persons along with their head pose. This way, it is possible to determine if a given person is looking towards the advertisement. While other similar methods use more complex setups, requiring a camera at each advertisement location, our method needs only a single (or a few) ceiling camera. Even though the apparent simplicity, the method can compute attention measures at each point of the scene.

}, author = {Manuel L{\'o}pez-Palma and Morros, J.R. and Javier Gago and Montserrat Corbal{\'a}n} } @inbook {bMohedano17, title = {Object Retrieval with Deep Convolutional Features}, booktitle = {Deep Learning for Image Processing Applications}, volume = {31}, number = {Advances in Parallel Computing}, year = {2017}, publisher = {IOS Press}, organization = {IOS Press}, address = {Amsterdam, The Netherlands}, abstract = {

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

}, issn = {978-1-61499-822-8 }, doi = {10.3233/978-1-61499-822-8-137}, url = {http://ebooks.iospress.nl/volumearticle/48028}, author = {Mohedano, Eva and Amaia Salvador and McGuinness, Kevin and Xavier Gir{\'o}-i-Nieto and O{\textquoteright}Connor, N. and Marqu{\'e}s, F.} } @article {x17, title = {One Perceptron to Rule Them All}, year = {2017}, abstract = {

Deep neural networks have boosted the convergence of multimedia data analytics in a unified framework shared by practitioners in natural language, vision and speech. Image captioning, lip reading or video sonorization are some of the first applications of a new and exciting field of research exploiting the generalisation properties of deep learning. Get the latest results on how convolutional and recurrent neural networks are combined to find the most hidden patterns in multimedia.

One Perceptron to Rule Them All (Re-Work Deep Learning Summit, London 2017) from Universitat Polit{\`e}cnica de Catalunya
} } @mastersthesis {xFerri16, title = {Object Tracking in Video with TensorFlow}, year = {2016}, abstract = {

[Project repo]

[Additional repo for setting up the environment]

}, author = {Ferri, Andrea}, editor = {Xavier Gir{\'o}-i-Nieto and Jordi Torres and Amaia Salvador} } @mastersthesis {xMasuda-Mora, title = {Open-Ended Visual Question-Answering}, year = {2016}, abstract = {

Advisors: Santiago de la Puente and Xavier Gir{\'o}-i-Nieto

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

Grade: A with honors (10/10.0)

This thesis studies methods to solve Visual Question-Answering (VQA) tasks with a Deep Learning framework.As a preliminary step, we explore Long Short-Term Memory (LSTM) networks used in Natural Language Processing (NLP) to tackle Question-Answering (text based). We then modify the previous model to accept an image as an input in addition to the question. For this purpose, we explore the VGG-16 and K-CNN convolutional neural networks to extract visual features from the image. These are merged with the word embedding or with a sentence embedding of the question to predict the answer. This work was successfully submitted to the Visual Question Answering Challenge 2016, where it achieved a 53,62\% of accuracy in the test dataset. The developed software has followed the best programming practices and Python code style, providing a consistent baseline in Keras for different configurations. The source code and models are publicly available at https://github.com/imatge-upc/vqa-2016-cvprw.

Open-ended Visual Question-Answering from Xavier Giro
}, url = {https://upcommons.upc.edu/handle/2117/89671}, author = {Masuda-Mora, Issey}, editor = {Pascual-deLaPuente, Santiago and Xavier Gir{\'o}-i-Nieto} } @article {aSalembier, title = {Optimum Graph-Cuts for Pruning Binary Partition Trees of Polarimetric SAR images}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, volume = {54}, year = {2016}, month = {05/2016}, pages = {5493 {\textendash} 5502}, abstract = {

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

}, author = {Salembier, P. and S. Foucher} } @article {aValero15, title = {Object recognition in hyperspectral images using Binary Partition Tree representation}, journal = {Pattern Recognition Letters}, volume = {56}, year = {2015}, month = {04/2015}, pages = {45-51}, abstract = {

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

}, issn = {0167-8655}, author = {Valero, S. and Salembier, P. and Chanussot, J.} } @conference {cMohedano, title = {Object segmentation in images using EEG signals}, booktitle = {ACM Multimedia}, year = {2014}, month = {11/2014}, address = {Orlando, Florida (USA)}, abstract = {

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

}, keywords = {Brain-computer interfaces, Electroencephalography, GrabCut algorithm, Interactive segmentation, Object segmentation, rapid serial visual presentation}, doi = {10.1145/2647868.2654896}, url = {http://arxiv.org/abs/1408.4363}, author = {Mohedano, Eva and Healy, Graham and Kevin McGuinness and Xavier Gir{\'o}-i-Nieto and O{\textquoteright}Connor, N. and Smeaton, Alan F.} } @conference {cValero13, title = {Object recognition in urban hyperspectral images using binary partition tree representation}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS{\textquoteright}2013}, year = {2013}, publisher = {IEEE}, organization = {IEEE}, address = {Melbourne, Australia}, author = {Valero, S. and Salembier, P. and Chanussot, J.} } @conference {cSuau12, title = {Oriented radial distribution on depth data: Application to the detection of end-effectors}, booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing}, year = {2012}, month = {03/2012}, address = {Kyoto, Japan}, abstract = {

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

}, doi = {10.1109/ICASSP.2012.6288002}, author = {Suau, X. and Ruiz-Hidalgo, J. and Casas, J.} } @conference {cPalou11, title = {Occlusion-based depth ordering on monocular images with binary partition tree}, booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2011}, year = {2011}, pages = {1093{\textendash}1096}, address = {Prague, Czech Republic}, doi = {0.1109/ICASSP.2011.5946598}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5946598\&tag=1}, author = {Palou, G. and Salembier, P.} } @conference {cVilaplana10, title = {Object detection and segmentation on a hierarchical region-based image representation}, booktitle = {2010 IEEE International Conference on Image Processing}, year = {2010}, pages = {3393{\textendash}3396}, isbn = {0-8194-2103-0}, url = {http://hdl.handle.net/2117/11435}, author = {Ver{\'o}nica Vilaplana and Marqu{\'e}s, F. and Le{\'o}n, M. and Gasull, A.} } @inbook {bSalembier08, title = {Operateur connexe et arbre des coupes}, booktitle = {Morphologie math{\'e}matique 1: approches deterministes}, year = {2008}, pages = {151{\textendash}172}, publisher = {Hermes, Lavoisier}, organization = {Hermes, Lavoisier}, edition = {L. Najman and H. Talbot (Eds.)}, isbn = {978-2-7462-1841-3}, author = {Salembier, P.} } @phdthesis {dSole06, title = {Optimization and Generalization of Lifting Schemes: Application to Lossless Image Compression}, year = {2006}, school = {Universitat Polit{\`e}cnica de Catalunya (UPC)}, type = {phd}, abstract = {

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

}, url = {http://hdl.handle.net/10803/6897}, author = {Sol{\'e}, J.} } @conference {cFerran05, title = {Object representation using colour, shape and structure criteria in a Binary Partition Tree}, booktitle = {IEEE International Conference on Image Processing}, year = {2005}, isbn = {0-7803-9135-7}, author = {Ferran, C. and Casas, J.} } @conference {cSalerno04, title = {Object recognition based on Binary Partition Trees}, booktitle = {IEEE International Conference on Image Processing}, year = {2004}, pages = {929{\textendash}932}, author = {Salerno, O. and M. Pard{\`a}s and Ver{\'o}nica Vilaplana and Marqu{\'e}s, F.} } @phdthesis {dMorros04, title = {Optimization of Segmentation Based Video Sequence Coding Techniques: Application to Content Based Functionalities}, year = {2004}, school = {Universitat Polit{\`e}cnica de Catalunya (UPC)}, type = {phd}, abstract = {

This work addresses the problem of video compression with content-based functionalities in the framework of segmentation-based video coding systems. Two major problems are considered. The first one is related with coding optimality in segmentation-based coding systems. Regarding this subject, the feasibility of a rate-distortion approach for a complete region-based coding system is shown. The second one is how to address content-based functionalities in the coding system proposed as a solution of the first problem. Optimality, as defined in the framework of rate-distortion theory, deals with obtaining a representation of the video sequence that leads to a minimum distortion of the coded signal for a given bit budget. In the case of segmentation-based coding systems this means to obtain an {\textquoteright}optimal{\textquoteright} partition together with the best coding technique for each region of this partition so that the result is optimal in an operational rate-distortion sense. The problem is formalized for independent, non-scalable coding. An algorithm to solve this problem is provided as well. This algorithms is applied to a specific segmentation-based coding system, the so called SESAME. In SESAME, each frame is segmented into a set of regions, that are coded independently. Segmentation involves both spatial and motion homogeneity criteria. To exploit temporal redundancy, a prediction for both the partition and the texture of the current frame is created by using motion information. The time evolution of each region is defined along the sequence (time tracking). The results are optimal (or near-optimal) for the given framework in a rate-distortion sense. The definition of the coding strategy involves a global optimization of the partition as well as of the coding technique/quality level for each region. Later, the investigation is also extended to the problem of video coding optimization in the framework of a scalable video coding system that can address content-based functionalities. The focus is set in the various types of content-based scalability and object tracking. The generality of the problem has also been extended by including the spatial and temporal dependencies between frames and scalability layers into the optimization schema. In this case the solution implies finding the optimal partition and set of quantizers for both the base and the enhancement layers. Due to the coding dependencies of the enhancement layer with respect to the base layer, the partition and the set of quantizers of the enhancement layer depend on the decisions made on the base layer. Also, a solution for the independent optimization problem (i.e. without tacking into account dependencies between different frames of scalability layers) has been proposed to reduce the computational complexity. These solutions are used to extend the SESAME coding system. The extended coding system, named XSESAME, supports different types of scalability (PSNR, Spatial and temporal) as well as content-based functionalities, such as content-based scalability and object tracking. Two different operating modes for region selection in the enhancement layer have been presented: One (supervised) aimed at providing content-based functionalities at the enhancement layer and the other (unsupervised) aimed at coding efficiency, without content-based functionalities. Integration of object tracking into the segmentation-based coding system is also investigated. In the general case, tracking is a very complex problem. If this capability has to be integrated into a coding system, additional problems arise due to conflicting requirements between coding efficiency and tracking accuracy. This is solved by using a double partition approach, where pure spatial criteria are used to re-segment the partition used for coding. The projection of the re-segmented partition results in more precise adaptation to object contours. A merging step is performed a posteriori to eliminate the excess of regions originated by the re-segmentation.

}, url = {http://hdl.handle.net/10803/6888}, author = {Morros, J.R.}, editor = {Marqu{\'e}s, F.} } @conference {cMarques02, title = {Object matching based on partition information}, booktitle = {IEEE International Conference on Image Processing}, year = {2002}, pages = {829{\textendash}832}, isbn = {0-7803-7623-4}, doi = {10.1109/icip.2002.1040079}, author = {Marqu{\'e}s, F. and M. Pard{\`a}s and Morros, J.R.} } @article {aMech02, title = {Objective evaluation criteria for 2-D shape estimation results of moving objects}, journal = {Eurasip Journal on Applied Signal Processing}, volume = {2002}, number = {4}, year = {2002}, pages = {401{\textendash}409}, issn = {1110-8657}, author = {Mech, R. and Marqu{\'e}s, F.} } @conference {cGasull02, title = {Oil Spills Detection in SAR Images using Mathematical Morphology}, booktitle = {11th European Signal Processing Conference (EUSIPCO 2002)}, year = {2002}, pages = {25{\textendash}28}, author = {Gasull, A. and F{\'a}bregas, F.X. and Jim{\'e}nez, J. and Marqu{\'e}s, F. and Moreno, V. and Herrero, M.} } @inbook {bSalembier02a, title = {Overview of MPEG-7 multimedia description schemes and schema tools}, booktitle = {Introduction to the mpeg-7: multimedia content description interface}, year = {2002}, pages = {83{\textendash}94}, publisher = {Wiley}, organization = {Wiley}, edition = {B. S. Manjunath, P. Salembier, T. Sikora (Eds.)}, chapter = {6}, isbn = {0471486787}, author = {Salembier, P. and Smith, J.} } @article {aSalembier02a, title = {Overview of the MPEG-7 Standard and of Future Challenges for Visual Information Analysis}, journal = {EURASIP Journal on Applied Signal Processing}, volume = {4}, number = {1}, year = {2002}, pages = {1{\textendash}11}, issn = {0165-1684}, author = {Salembier, P.} } @conference {cBescos01, title = {An open integrated system for video indexing}, booktitle = {International Workshop on Content-Based Multimedia Indexing}, year = {2001}, pages = {322{\textendash}333}, author = {Bescos, J. and Torres, L. and Menendez, J. and Vil{\`a}, J. and Cisneros, G. and Marqu{\'e}s, F. and Cabrera, J. and Mart{\'\i}nez, J.} } @conference {cSalembier01a, title = {An overview of MPEG-7 Multimedia Description Schemes and of future visual information analysis challenges for content-based indexing}, booktitle = {International Workshop on Content-Based Multimedia Indexing, CBMI 2001}, year = {2001}, address = {Brescia, Italy}, author = {Salembier, P.} } @conference {cSalembier01, title = {An overview of the MPEG-7 standard and of future challenges for visual information analysis}, booktitle = {Workshop on Image Analysis for Multimedia Services, WIAMIS 2001}, year = {2001}, address = {Tampere, Finland}, author = {Salembier, P.} } @conference {cSayrol99, title = {Optimum Watermark Detection in Color Images}, booktitle = {1999 IEEE International Conference on Image Processing}, year = {1999}, pages = {1{\textendash}5}, author = {Elisa Sayrol and Vidal, J. and Cabanillas, S. and Santamaria, S.} } @conference {cVidal98a, title = {Optimum Watermark Detection and Embedding in Digital Images}, booktitle = {1998 IEEE Second Workshop on Multimedia Signal Processing}, year = {1998}, pages = {285{\textendash}290}, isbn = {0-7803-4919-9}, author = {Vidal, J. and Elisa Sayrol} } @article {aPardas97, title = {Object-base image coding}, journal = {Vistas in astronomy}, volume = {41}, number = {3}, year = {1997}, pages = {455{\textendash}461}, issn = {0083-6656}, author = {M. Pard{\`a}s} } @conference {cSerra94 , title = {Op{\'e}rateurs connexes et pyramides}, booktitle = {In Proc. of RFIA}, year = {1994}, address = {Paris, France}, author = {Serra, J. and Salembier, P.} } @conference {cSalembier93e, title = {Object-based image coding with morphological segmentation and efficient contour coding}, booktitle = {IEEE International Conference on Signal Processing, ICSP{\textquoteright}93}, year = {1993}, address = {Beijing, China}, author = {Salembier, P. and Marqu{\'e}s, F.} } @conference {cMarques91b, title = {Obtencion de un esqueleto morfologico sin puntos redundantes}, booktitle = {VI Simposium Nacional de la Uni{\'o}n Cient{\'\i}fica Internacional de Radio}, year = {1991}, pages = {980{\textendash}984}, author = {Marqu{\'e}s, F. and Gasull, A. and Torres, L.} }