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Eduard Vazquez; Theo Gevers; M. Lucassen; Joost Van de Weijer; Ramon Baldrich |
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Title |
Saliency of Color Image Derivatives: A Comparison between Computational Models and Human Perception |
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Journal Article |
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2010 |
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Journal of the Optical Society of America A |
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JOSA A |
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27 |
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3 |
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613–621 |
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In this paper, computational methods are proposed to compute color edge saliency based on the information content of color edges. The computational methods are evaluated on bottom-up saliency in a psychophysical experiment, and on a more complex task of salient object detection in real-world images. The psychophysical experiment demonstrates the relevance of using information theory as a saliency processing model and that the proposed methods are significantly better in predicting color saliency (with a human-method correspondence up to 74.75% and an observer agreement of 86.8%) than state-of-the-art models. Furthermore, results from salient object detection confirm that an early fusion of color and contrast provide accurate performance to compute visual saliency with a hit rate up to 95.2%. |
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ISE;CIC |
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CAT @ cat @ VGL2010 |
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1275 |
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Arjan Gijsenij; Theo Gevers; Joost Van de Weijer |
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Title |
Computational Color Constancy: Survey and Experiments |
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Journal Article |
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2011 |
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IEEE Transactions on Image Processing |
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TIP |
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20 |
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9 |
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2475-2489 |
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computational color constancy;computer vision application;gamut-based method;learning-based method;static method;colour vision;computer vision;image colour analysis;learning (artificial intelligence);lighting |
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Computational color constancy is a fundamental prerequisite for many computer vision applications. This paper presents a survey of many recent developments and state-of-the- art methods. Several criteria are proposed that are used to assess the approaches. A taxonomy of existing algorithms is proposed and methods are separated in three groups: static methods, gamut-based methods and learning-based methods. Further, the experimental setup is discussed including an overview of publicly available data sets. Finally, various freely available methods, of which some are considered to be state-of-the-art, are evaluated on two data sets. |
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1057-7149 |
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ISE;CIC |
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Admin @ si @ GGW2011 |
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1717 |
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Jorge Bernal; Aymeric Histace; Marc Masana; Quentin Angermann; Cristina Sanchez Montes; Cristina Rodriguez de Miguel; Maroua Hammami; Ana Garcia Rodriguez; Henry Cordova; Olivier Romain; Gloria Fernandez Esparrach; Xavier Dray; F. Javier Sanchez |
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Title |
Polyp Detection Benchmark in Colonoscopy Videos using GTCreator: A Novel Fully Configurable Tool for Easy and Fast Annotation of Image Databases |
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Conference Article |
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2018 |
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32nd International Congress and Exhibition on Computer Assisted Radiology & Surgery |
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CARS |
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ISE; MV; 600.119 |
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Admin @ si @ BHM2018 |
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3089 |
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Mikhail Mozerov; Joost Van de Weijer |
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Title |
Accurate stereo matching by two step global optimization |
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2015 |
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IEEE Transactions on Image Processing |
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TIP |
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24 |
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3 |
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1153-1163 |
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In stereo matching cost filtering methods and energy minimization algorithms are considered as two different techniques. Due to their global extend energy minimization methods obtain good stereo matching results. However, they tend to fail in occluded regions, in which cost filtering approaches obtain better results. In this paper we intend to combine both approaches with the aim to improve overall stereo matching results. We show that a global optimization with a fully connected model can be solved by cost fil tering methods. Based on this observation we propose to perform stereo matching as a two-step energy minimization algorithm. We consider two MRF models: a fully connected model defined on the complete set of pixels in an image and a conventional locally connected model. We solve the energy minimization problem for the fully connected model, after which the marginal function of the solution is used as the unary potential in the locally connected MRF model. Experiments on the Middlebury stereo datasets show that the proposed method achieves state-of-the-arts results. |
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1057-7149 |
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ISE; LAMP; 600.079; 600.078 |
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Admin @ si @ MoW2015a |
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2568 |
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Author |
Pau Rodriguez; Miguel Angel Bautista; Sergio Escalera; Jordi Gonzalez |
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Title |
Beyond Oneshot Encoding: lower dimensional target embedding |
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Journal Article |
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2018 |
Publication |
Image and Vision Computing |
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IMAVIS |
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75 |
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21-31 |
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Error correcting output codes; Output embeddings; Deep learning; Computer vision |
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Target encoding plays a central role when learning Convolutional Neural Networks. In this realm, one-hot encoding is the most prevalent strategy due to its simplicity. However, this so widespread encoding schema assumes a flat label space, thus ignoring rich relationships existing among labels that can be exploited during training. In large-scale datasets, data does not span the full label space, but instead lies in a low-dimensional output manifold. Following this observation, we embed the targets into a low-dimensional space, drastically improving convergence speed while preserving accuracy. Our contribution is two fold: (i) We show that random projections of the label space are a valid tool to find such lower dimensional embeddings, boosting dramatically convergence rates at zero computational cost; and (ii) we propose a normalized eigenrepresentation of the class manifold that encodes the targets with minimal information loss, improving the accuracy of random projections encoding while enjoying the same convergence rates. Experiments on CIFAR-100, CUB200-2011, Imagenet, and MIT Places demonstrate that the proposed approach drastically improves convergence speed while reaching very competitive accuracy rates. |
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ISE; HuPBA; 600.098; 602.133; 602.121; 600.119 |
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Admin @ si @ RBE2018 |
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3120 |
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Author |
Anastasios Doulamis; Nikolaos Doulamis; Marco Bertini; Jordi Gonzalez; Thomas B. Moeslund |
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Title |
Introduction to the Special Issue on the Analysis and Retrieval of Events/Actions and Workflows in Video Streams |
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Journal Article |
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2016 |
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Multimedia Tools and Applications |
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MTAP |
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75 |
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22 |
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14985-14990 |
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ISE; HUPBA |
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no |
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Admin @ si @ DDB2016 |
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2934 |
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Author |
Hunor Laczko; Meysam Madadi; Sergio Escalera; Jordi Gonzalez |
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Title |
A Generative Multi-Resolution Pyramid and Normal-Conditioning 3D Cloth Draping |
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Conference Article |
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2024 |
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Winter Conference on Applications of Computer Vision |
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8709-8718 |
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RGB cloth generation has been deeply studied in the related literature, however, 3D garment generation remains an open problem. In this paper, we build a conditional variational autoencoder for 3D garment generation and draping. We propose a pyramid network to add garment details progressively in a canonical space, i.e. unposing and unshaping the garments w.r.t. the body. We study conditioning the network on surface normal UV maps, as an intermediate representation, which is an easier problem to optimize than 3D coordinates. Our results on two public datasets, CLOTH3D and CAPE, show that our model is robust, controllable in terms of detail generation by the use of multi-resolution pyramids, and achieves state-of-the-art results that can highly generalize to unseen garments, poses, and shapes even when training with small amounts of data. |
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Waikoloa; Hawai; USA; January 2024 |
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WACV |
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ISE; HUPBA |
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no |
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Admin @ si @ LME2024 |
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3996 |
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Author |
Noha Elfiky; Fahad Shahbaz Khan; Joost Van de Weijer; Jordi Gonzalez |
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Title |
Discriminative Compact Pyramids for Object and Scene Recognition |
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2012 |
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Pattern Recognition |
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PR |
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45 |
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4 |
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1627-1636 |
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Spatial pyramids have been successfully applied to incorporating spatial information into bag-of-words based image representation. However, a major drawback is that it leads to high dimensional image representations. In this paper, we present a novel framework for obtaining compact pyramid representation. First, we investigate the usage of the divisive information theoretic feature clustering (DITC) algorithm in creating a compact pyramid representation. In many cases this method allows us to reduce the size of a high dimensional pyramid representation up to an order of magnitude with little or no loss in accuracy. Furthermore, comparison to clustering based on agglomerative information bottleneck (AIB) shows that our method obtains superior results at significantly lower computational costs. Moreover, we investigate the optimal combination of multiple features in the context of our compact pyramid representation. Finally, experiments show that the method can obtain state-of-the-art results on several challenging data sets. |
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0031-3203 |
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ISE; CAT;CIC |
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Admin @ si @ EKW2012 |
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1807 |
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Ariel Amato; Felipe Lumbreras; Angel Sappa |
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A General-purpose Crowdsourcing Platform for Mobile Devices |
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2014 |
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9th International Conference on Computer Vision Theory and Applications |
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3 |
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211-215 |
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Crowdsourcing Platform; Mobile Crowdsourcing |
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This paper presents details of a general purpose micro-task on-demand platform based on the crowdsourcing philosophy. This platform was specifically developed for mobile devices in order to exploit the strengths of such devices; namely: i) massivity, ii) ubiquity and iii) embedded sensors. The combined use of mobile platforms and the crowdsourcing model allows to tackle from the simplest to the most complex tasks. Users experience is the highlighted feature of this platform (this fact is extended to both task-proposer and tasksolver). Proper tools according with a specific task are provided to a task-solver in order to perform his/her job in a simpler, faster and appealing way. Moreover, a task can be easily submitted by just selecting predefined templates, which cover a wide range of possible applications. Examples of its usage in computer vision and computer games are provided illustrating the potentiality of the platform. |
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Lisboa; Portugal; January 2014 |
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VISAPP |
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ISE; ADAS; 600.054; 600.055; 600.076; 600.078 |
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Admin @ si @ ALS2014 |
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2478 |
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Ariel Amato; Ivan Huerta; Mikhail Mozerov; Xavier Roca; Jordi Gonzalez |
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Title |
Moving Cast Shadows Detection Methods for Video Surveillance Applications |
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2014 |
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Augmented Vision and Reality |
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6 |
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23-47 |
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Moving cast shadows are a major concern in today’s performance from broad range of many vision-based surveillance applications because they highly difficult the object classification task. Several shadow detection methods have been reported in the literature during the last years. They are mainly divided into two domains. One usually works with static images, whereas the second one uses image sequences, namely video content. In spite of the fact that both cases can be analogously analyzed, there is a difference in the application field. The first case, shadow detection methods can be exploited in order to obtain additional geometric and semantic cues about shape and position of its casting object (‘shape from shadows’) as well as the localization of the light source. While in the second one, the main purpose is usually change detection, scene matching or surveillance (usually in a background subtraction context). Shadows can in fact modify in a negative way the shape and color of the target object and therefore affect the performance of scene analysis and interpretation in many applications. This chapter wills mainly reviews shadow detection methods as well as their taxonomies related with the second case, thus aiming at those shadows which are associated with moving objects (moving shadows). |
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Springer Berlin Heidelberg |
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2190-5916 |
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978-3-642-37840-9 |
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ISE; 605.203; 600.049; 302.018; 302.012; 600.078 |
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Admin @ si @ AHM2014 |
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2223 |
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Marc Castello; Jordi Gonzalez; Ariel Amato; Pau Baiget; Carles Fernandez; Josep M. Gonfaus; Ramon Mollineda; Marco Pedersoli; Nicolas Perez de la Blanca; Xavier Roca |
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Exploiting Multimodal Interaction Techniques for Video-Surveillance |
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2013 |
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Multimodal Interaction in Image and Video Applications Intelligent Systems Reference Library |
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48 |
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8 |
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135-151 |
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In this paper we present an example of a video surveillance application that exploits Multimodal Interactive (MI) technologies. The main objective of the so-called VID-Hum prototype was to develop a cognitive artificial system for both the detection and description of a particular set of human behaviours arising from real-world events. The main procedure of the prototype described in this chapter entails: (i) adaptation, since the system adapts itself to the most common behaviours (qualitative data) inferred from tracking (quantitative data) thus being able to recognize abnormal behaviors; (ii) feedback, since an advanced interface based on Natural Language understanding allows end-users the communicationwith the prototype by means of conceptual sentences; and (iii) multimodality, since a virtual avatar has been designed to describe what is happening in the scene, based on those textual interpretations generated by the prototype. Thus, the MI methodology has provided an adequate framework for all these cooperating processes. |
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Springer Berlin Heidelberg |
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1868-4394 |
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978-3-642-35931-6 |
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ISE; 605.203; 600.049 |
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CGA2013 |
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2222 |
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Carles Fernandez; Jordi Gonzalez; Joao Manuel R. S. Taveres; Xavier Roca |
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Title |
Towards Ontological Cognitive System |
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2013 |
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Topics in Medical Image Processing and Computational Vision |
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8 |
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87-99 |
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The increasing ubiquitousness of digital information in our daily lives has positioned video as a favored information vehicle, and given rise to an astonishing generation of social media and surveillance footage. This raises a series of technological demands for automatic video understanding and management, which together with the compromising attentional limitations of human operators, have motivated the research community to guide its steps towards a better attainment of such capabilities. As a result, current trends on cognitive vision promise to recognize complex events and self-adapt to different environments, while managing and integrating several types of knowledge. Future directions suggest to reinforce the multi-modal fusion of information sources and the communication with end-users. |
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Springer Netherlands |
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2212-9391 |
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978-94-007-0725-2 |
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ISE; 605.203; 302.018; 600.049 |
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Admin @ si @ FGT2013 |
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2287 |
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Francisco Javier Orozco; Ognjen Rudovic; Jordi Gonzalez; Maja Pantic |
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Hierarchical On-line Appearance-Based Tracking for 3D Head Pose, Eyebrows, Lips, Eyelids and Irises |
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Journal Article |
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2013 |
Publication |
Image and Vision Computing |
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IMAVIS |
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31 |
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4 |
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322-340 |
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On-line appearance models; Levenberg–Marquardt algorithm; Line-search optimization; 3D face tracking; Facial action tracking; Eyelid tracking; Iris tracking |
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In this paper, we propose an On-line Appearance-Based Tracker (OABT) for simultaneous tracking of 3D head pose, lips, eyebrows, eyelids and irises in monocular video sequences. In contrast to previously proposed tracking approaches, which deal with face and gaze tracking separately, our OABT can also be used for eyelid and iris tracking, as well as 3D head pose, lips and eyebrows facial actions tracking. Furthermore, our approach applies an on-line learning of changes in the appearance of the tracked target. Hence, the prior training of appearance models, which usually requires a large amount of labeled facial images, is avoided. Moreover, the proposed method is built upon a hierarchical combination of three OABTs, which are optimized using a Levenberg–Marquardt Algorithm (LMA) enhanced with line-search procedures. This, in turn, makes the proposed method robust to changes in lighting conditions, occlusions and translucent textures, as evidenced by our experiments. Finally, the proposed method achieves head and facial actions tracking in real-time. |
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Elsevier |
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ISE; 605.203; 302.012; 302.018; 600.049 |
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ORG2013 |
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2221 |
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Pau Rodriguez; Jordi Gonzalez; Jordi Cucurull; Josep M. Gonfaus; Xavier Roca |
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Regularizing CNNs with Locally Constrained Decorrelations |
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2017 |
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5th International Conference on Learning Representations |
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Toulon; France; April 2017 |
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ISE; 602.143; 600.119; 600.098 |
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Admin @ si @ RGC2017 |
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2927 |
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Marco Pedersoli; Jordi Gonzalez; Xu Hu; Xavier Roca |
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Toward Real-Time Pedestrian Detection Based on a Deformable Template Model |
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2014 |
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IEEE Transactions on Intelligent Transportation Systems |
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TITS |
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1 |
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355-364 |
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Most advanced driving assistance systems already include pedestrian detection systems. Unfortunately, there is still a tradeoff between precision and real time. For a reliable detection, excellent precision-recall such a tradeoff is needed to detect as many pedestrians as possible while, at the same time, avoiding too many false alarms; in addition, a very fast computation is needed for fast reactions to dangerous situations. Recently, novel approaches based on deformable templates have been proposed since these show a reasonable detection performance although they are computationally too expensive for real-time performance. In this paper, we present a system for pedestrian detection based on a hierarchical multiresolution part-based model. The proposed system is able to achieve state-of-the-art detection accuracy due to the local deformations of the parts while exhibiting a speedup of more than one order of magnitude due to a fast coarse-to-fine inference technique. Moreover, our system explicitly infers the level of resolution available so that the detection of small examples is feasible with a very reduced computational cost. We conclude this contribution by presenting how a graphics processing unit-optimized implementation of our proposed system is suitable for real-time pedestrian detection in terms of both accuracy and speed. |
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1524-9050 |
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ISE; 601.213; 600.078 |
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2350 |
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