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Author Michal Drozdzal; Santiago Segui; Petia Radeva; Jordi Vitria; Laura Igual edit  openurl
  Title System and Method for Displaying Motility Events in an in Vivo Image Stream Type Patent
  Year 2011 Publication US 61/592,786 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Given Imaging  
  Corporate Author US Patent Office Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title (up)  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MILAB; OR;MV Approved no  
  Call Number Admin @ si @ DSR2011 Serial 1897  
Permanent link to this record
 

 
Author Alejandro Gonzalez Alzate edit  openurl
  Title Evaluation of spatiotemporal descriptors for pedestrian detection in video sequences Type Report
  Year 2011 Publication CVC Technical Report Abbreviated Journal  
  Volume 166 Issue Pages  
  Keywords  
  Abstract  
  Address Bellaterra (Spain)  
  Corporate Author Computer Vision Center Thesis Master's thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title (up)  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number Admin @ si @ Gon2011 Serial 1932  
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Author Yainuvis Socarras edit  openurl
  Title Image segmentation for improving pedestrian detection Type Report
  Year 2011 Publication CVC Technical Report Abbreviated Journal  
  Volume 167 Issue Pages  
  Keywords  
  Abstract  
  Address Bellaterra (Spain)  
  Corporate Author Computer Vision Center Thesis Master's thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title (up)  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ADAS; Approved no  
  Call Number Admin @ si @ Soc2011 Serial 1933  
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Author Maria del Camp Davesa edit  openurl
  Title Human action categorization in image sequences Type Report
  Year 2011 Publication CVC Technical Report Abbreviated Journal  
  Volume 169 Issue Pages  
  Keywords  
  Abstract  
  Address Bellaterra (Spain)  
  Corporate Author Computer Vision Center Thesis Master's thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title (up)  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes CiC;CIC Approved no  
  Call Number Admin @ si @ Dav2011 Serial 1934  
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Author Marçal Rusiñol; R.Roset; Josep Llados; C.Montaner edit  openurl
  Title Automatic Index Generation of Digitized Map Series by Coordinate Extraction and Interpretation Type Conference Article
  Year 2011 Publication In Proceedings of the Sixth International Workshop on Digital Technologies in Cartographic Heritage Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title (up)  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CartoHerit  
  Notes DAG Approved no  
  Call Number Admin @ si @ RRL2011b Serial 1978  
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Author Sergio Vera; Debora Gil; Agnes Borras; F. Javier Sanchez; Frederic Perez; Marius G. Linguraru edit  openurl
  Title Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs Type Conference Article
  Year 2011 Publication Workshop on Computational and Clinical Applications in Abdominal Imaging Abbreviated Journal  
  Volume 7029 Issue Pages 223-230  
  Keywords  
  Abstract Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs, exploring the use of medial manifolds for the representation of multi-organ relations.  
  Address Nice, France  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor In H. Yoshida et al  
  Language Summary Language Original Title (up)  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ABDI  
  Notes IAM; MV Approved no  
  Call Number VGB2011 Serial 2036  
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Author Jaime Moreno; Xavier Otazu edit  doi
isbn  openurl
  Title Image compression algorithm based on Hilbert scanning of embedded quadTrees: an introduction of the Hi-SET coder Type Conference Article
  Year 2011 Publication IEEE International Conference on Multimedia and Expo Abbreviated Journal  
  Volume Issue Pages 1-6  
  Keywords  
  Abstract In this work we present an effective and computationally simple algorithm for image compression based on Hilbert Scanning of Embedded quadTrees (Hi-SET). It allows to represent an image as an embedded bitstream along a fractal function. Embedding is an important feature of modern image compression algorithms, in this way Salomon in [1, pg. 614] cite that another feature and perhaps a unique one is the fact of achieving the best quality for the number of bits input by the decoder at any point during the decoding. Hi-SET possesses also this latter feature. Furthermore, the coder is based on a quadtree partition strategy, that applied to image transformation structures such as discrete cosine or wavelet transform allows to obtain an energy clustering both in frequency and space. The coding algorithm is composed of three general steps, using just a list of significant pixels. The implementation of the proposed coder is developed for gray-scale and color image compression. Hi-SET compressed images are, on average, 6.20dB better than the ones obtained by other compression techniques based on the Hilbert scanning. Moreover, Hi-SET improves the image quality in 1.39dB and 1.00dB in gray-scale and color compression, respectively, when compared with JPEG2000 coder.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title (up)  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1945-7871 ISBN 978-1-61284-348-3 Medium  
  Area Expedition Conference ICME  
  Notes CIC Approved no  
  Call Number Admin @ si @ MoO2011a Serial 2176  
Permanent link to this record
 

 
Author Jaime Moreno; Xavier Otazu edit  openurl
  Title Image coder based on Hilbert scanning of embedded quadTrees Type Conference Article
  Year 2011 Publication Data Compression Conference Abbreviated Journal  
  Volume Issue Pages 470-470  
  Keywords  
  Abstract In this work we present an effective and computationally simple algorithm for image compression based on Hilbert Scanning of Embedded quadTrees (Hi-SET). It allows to represent an image as an embedded bitstream along a fractal function. Embedding is an important feature of modern image compression algorithms, in this way Salomon in [1, pg. 614] cite that another feature and perhaps a unique one is the fact of achieving the best quality for the number of bits input by the decoder at any point during the decoding. Hi-SET possesses also this latter feature. Furthermore, the coder is based on a quadtree partition strategy, that applied to image transformation structures such as discrete cosine or wavelet transform allows to obtain an energy clustering both in frequency and space. The coding algorithm is composed of three general steps, using just a list of significant pixels.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title (up)  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference DCC  
  Notes CIC Approved no  
  Call Number Admin @ si @ MoO2011b Serial 2177  
Permanent link to this record
 

 
Author Mirko Arnold; Stephan Ameling; Anarta Ghosh; Gerard Lacey edit  doi
openurl 
  Title Quality Improvement of Endoscopy Videos Type Conference Article
  Year 2011 Publication Proceedings of the 8th IASTED International Conference on Biomedical Engineering Abbreviated Journal  
  Volume 723 Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title (up)  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area 800 Expedition Conference  
  Notes MV Approved no  
  Call Number fernando @ fernando @ Serial 2426  
Permanent link to this record
 

 
Author Victor Ponce; Mario Gorga; Xavier Baro; Petia Radeva; Sergio Escalera edit  url
openurl 
  Title Análisis de la expresión oral y gestual en proyectos fin de carrera vía un sistema de visión artificial Type Journal Article
  Year 2011 Publication ReVisión Abbreviated Journal  
  Volume 4 Issue 1 Pages  
  Keywords  
  Abstract La comunicación y expresión oral es una competencia de especial relevancia en el EEES. No obstante, en muchas enseñanzas superiores la puesta en práctica de esta competencia ha sido relegada principalmente a la presentación de proyectos fin de carrera. Dentro de un proyecto de innovación docente, se ha desarrollado una herramienta informática para la extracción de información objetiva para el análisis de la expresión oral y gestual de los alumnos. El objetivo es dar un “feedback” a los estudiantes que les permita mejorar la calidad de sus presentaciones. El prototipo inicial que se presenta en este trabajo permite extraer de forma automática información audiovisual y analizarla mediante técnicas de aprendizaje. El sistema ha sido aplicado a 15 proyectos fin de carrera y 15 exposiciones dentro de una asignatura de cuarto curso. Los resultados obtenidos muestran la viabilidad del sistema para sugerir factores que ayuden tanto en el éxito de la comunicación así como en los criterios de evaluación.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title (up)  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1989-1199 ISBN Medium  
  Area Expedition Conference  
  Notes HuPBA; MILAB;MV Approved no  
  Call Number Admin @ si @ PGB2011d Serial 2514  
Permanent link to this record
 

 
Author Muhammad Anwer Rao; David Vazquez; Antonio Lopez edit   pdf
doi  isbn
openurl 
  Title Color Contribution to Part-Based Person Detection in Different Types of Scenarios Type Conference Article
  Year 2011 Publication 14th International Conference on Computer Analysis of Images and Patterns Abbreviated Journal  
  Volume 6855 Issue II Pages 463-470  
  Keywords Pedestrian Detection; Color  
  Abstract Camera-based person detection is of paramount interest due to its potential applications. The task is diffcult because the great variety of backgrounds (scenarios, illumination) in which persons are present, as well as their intra-class variability (pose, clothe, occlusion). In fact, the class person is one of the included in the popular PASCAL visual object classes (VOC) challenge. A breakthrough for this challenge, regarding person detection, is due to Felzenszwalb et al. These authors proposed a part-based detector that relies on histograms of oriented gradients (HOG) and latent support vector machines (LatSVM) to learn a model of the whole human body and its constitutive parts, as well as their relative position. Since the approach of Felzenszwalb et al. appeared new variants have been proposed, usually giving rise to more complex models. In this paper, we focus on an issue that has not attracted suficient interest up to now. In particular, we refer to the fact that HOG is usually computed from RGB color space, but other possibilities exist and deserve the corresponding investigation. In this paper we challenge RGB space with the opponent color space (OPP), which is inspired in the human vision system.We will compute the HOG on top of OPP, then we train and test the part-based human classifer by Felzenszwalb et al. using PASCAL VOC challenge protocols and person database. Our experiments demonstrate that OPP outperforms RGB. We also investigate possible differences among types of scenarios: indoor, urban and countryside. Interestingly, our experiments suggest that the beneficts of OPP with respect to RGB mainly come for indoor and countryside scenarios, those in which the human visual system was designed by evolution.  
  Address Seville, Spain  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Berlin Heidelberg Editor P. Real, D. Diaz, H. Molina, A. Berciano, W. Kropatsch  
  Language English Summary Language english Original Title (up) Color Contribution to Part-Based Person Detection in Different Types of Scenarios  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-23677-8 Medium  
  Area Expedition Conference CAIP  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ RVL2011b Serial 1665  
Permanent link to this record
 

 
Author Muhammad Anwer Rao; David Vazquez; Antonio Lopez edit   pdf
doi  isbn
openurl 
  Title Opponent Colors for Human Detection Type Conference Article
  Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 6669 Issue Pages 363-370  
  Keywords Pedestrian Detection; Color; Part Based Models  
  Abstract Human detection is a key component in fields such as advanced driving assistance and video surveillance. However, even detecting non-occluded standing humans remains a challenge of intensive research. Finding good features to build human models for further detection is probably one of the most important issues to face. Currently, shape, texture and motion features have deserve extensive attention in the literature. However, color-based features, which are important in other domains (e.g., image categorization), have received much less attention. In fact, the use of RGB color space has become a kind of choice by default. The focus has been put in developing first and second order features on top of RGB space (e.g., HOG and co-occurrence matrices, resp.). In this paper we evaluate the opponent colors (OPP) space as a biologically inspired alternative for human detection. In particular, by feeding OPP space in the baseline framework of Dalal et al. for human detection (based on RGB, HOG and linear SVM), we will obtain better detection performance than by using RGB space. This is a relevant result since, up to the best of our knowledge, OPP space has not been previously used for human detection. This suggests that in the future it could be worth to compute co-occurrence matrices, self-similarity features, etc., also on top of OPP space, i.e., as we have done with HOG in this paper.  
  Address Las Palmas de Gran Canaria. Spain  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Berlin Heidelberg Editor J. Vitria; J.M. Sanches; M. Hernandez  
  Language English Summary Language English Original Title (up) Opponent Colors for Human Detection  
  Series Editor Series Title Lecture Notes on Computer Science Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-21256-7 Medium  
  Area Expedition Conference IbPRIA  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ RVL2011a Serial 1666  
Permanent link to this record
 

 
Author David Vazquez; Antonio Lopez; Daniel Ponsa; Javier Marin edit   pdf
doi  isbn
openurl 
  Title Virtual Worlds and Active Learning for Human Detection Type Conference Article
  Year 2011 Publication 13th International Conference on Multimodal Interaction Abbreviated Journal  
  Volume Issue Pages 393-400  
  Keywords Pedestrian Detection; Human detection; Virtual; Domain Adaptation; Active Learning  
  Abstract Image based human detection is of paramount interest due to its potential applications in fields such as advanced driving assistance, surveillance and media analysis. However, even detecting non-occluded standing humans remains a challenge of intensive research. The most promising human detectors rely on classifiers developed in the discriminative paradigm, i.e., trained with labelled samples. However, labeling is a manual intensive step, especially in cases like human detection where it is necessary to provide at least bounding boxes framing the humans for training. To overcome such problem, some authors have proposed the use of a virtual world where the labels of the different objects are obtained automatically. This means that the human models (classifiers) are learnt using the appearance of rendered images, i.e., using realistic computer graphics. Later, these models are used for human detection in images of the real world. The results of this technique are surprisingly good. However, these are not always as good as the classical approach of training and testing with data coming from the same camera, or similar ones. Accordingly, in this paper we address the challenge of using a virtual world for gathering (while playing a videogame) a large amount of automatically labelled samples (virtual humans and background) and then training a classifier that performs equal, in real-world images, than the one obtained by equally training from manually labelled real-world samples. For doing that, we cast the problem as one of domain adaptation. In doing so, we assume that a small amount of manually labelled samples from real-world images is required. To collect these labelled samples we propose a non-standard active learning technique. Therefore, ultimately our human model is learnt by the combination of virtual and real world labelled samples (Fig. 1), which has not been done before. We present quantitative results showing that this approach is valid.  
  Address Alicante, Spain  
  Corporate Author Thesis  
  Publisher ACM DL Place of Publication New York, NY, USA, USA Editor  
  Language English Summary Language English Original Title (up) Virtual Worlds and Active Learning for Human Detection  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-4503-0641-6 Medium  
  Area Expedition Conference ICMI  
  Notes ADAS Approved yes  
  Call Number ADAS @ adas @ VLP2011a Serial 1683  
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