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Author Jordi Roca; C. Alejandro Parraga; Maria Vanrell edit  url
openurl 
  Title Categorical Focal Colours are Structurally Invariant Under Illuminant Changes Type Conference Article
  Year 2011 Publication European Conference on Visual Perception Abbreviated Journal  
  Volume Issue Pages 196  
  Keywords  
  Abstract The visual system perceives the colour of surfaces approximately constant under changes of illumination. In this work, we investigate how stable is the perception of categorical \“focal\” colours and their interrelations with varying illuminants and simple chromatic backgrounds. It has been proposed that best examples of colour categories across languages cluster in small regions of the colour space and are restricted to a set of 11 basic terms (Kay and Regier, 2003 Proceedings of the National Academy of Sciences of the USA 100 9085\–9089). Following this, we developed a psychophysical paradigm that exploits the ability of subjects to reliably reproduce the most representative examples of each category, adjusting multiple test patches embedded in a coloured Mondrian. The experiment was run on a CRT monitor (inside a dark room) under various simulated illuminants. We modelled the recorded data for each subject and adapted state as a 3D interconnected structure (graph) in Lab space. The graph nodes were the subject\’s focal colours at each adaptation state. The model allowed us to get a better distance measure between focal structures under different illuminants. We found that perceptual focal structures tend to be preserved better than the structures of the physical \“ideal\” colours under illuminant changes.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language (up) Summary Language Original Title  
  Series Editor Series Title Perception 40 Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ECVP  
  Notes CIC Approved no  
  Call Number Admin @ si @ RPV2011 Serial 1867  
Permanent link to this record
 

 
Author Sergio Escalera; Ana Puig; Oscar Amoros; Maria Salamo edit  doi
openurl 
  Title Intelligent GPGPU Classification in Volume Visualization: a framework based on Error-Correcting Output Codes Type Journal Article
  Year 2011 Publication Computer Graphics Forum Abbreviated Journal CGF  
  Volume 30 Issue 7 Pages 2107-2115  
  Keywords  
  Abstract IF JCR 1.455 2010 25/99
In volume visualization, the definition of the regions of interest is inherently an iterative trial-and-error process finding out the best parameters to classify and render the final image. Generally, the user requires a lot of expertise to analyze and edit these parameters through multi-dimensional transfer functions. In this paper, we present a framework of intelligent methods to label on-demand multiple regions of interest. These methods can be split into a two-level GPU-based labelling algorithm that computes in time of rendering a set of labelled structures using the Machine Learning Error-Correcting Output Codes (ECOC) framework. In a pre-processing step, ECOC trains a set of Adaboost binary classifiers from a reduced pre-labelled data set. Then, at the testing stage, each classifier is independently applied on the features of a set of unlabelled samples and combined to perform multi-class labelling. We also propose an alternative representation of these classifiers that allows to highly parallelize the testing stage. To exploit that parallelism we implemented the testing stage in GPU-OpenCL. The empirical results on different data sets for several volume structures shows high computational performance and classification accuracy.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language (up) Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MILAB; HuPBA Approved no  
  Call Number Admin @ si @ EPA2011 Serial 1881  
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Author Laura Igual; Joan Carles Soliva; Antonio Hernandez; Sergio Escalera; Xavier Jimenez ; Oscar Vilarroya; Petia Radeva edit  doi
openurl 
  Title A fully-automatic caudate nucleus segmentation of brain MRI: Application in volumetric analysis of pediatric attention-deficit/hyperactivity disorder Type Journal Article
  Year 2011 Publication BioMedical Engineering Online Abbreviated Journal BEO  
  Volume 10 Issue 105 Pages 1-23  
  Keywords Brain caudate nucleus; segmentation; MRI; atlas-based strategy; Graph Cut framework  
  Abstract Background
Accurate automatic segmentation of the caudate nucleus in magnetic resonance images (MRI) of the brain is of great interest in the analysis of developmental disorders. Segmentation methods based on a single atlas or on multiple atlases have been shown to suitably localize caudate structure. However, the atlas prior information may not represent the structure of interest correctly. It may therefore be useful to introduce a more flexible technique for accurate segmentations.

Method
We present Cau-dateCut: a new fully-automatic method of segmenting the caudate nucleus in MRI. CaudateCut combines an atlas-based segmentation strategy with the Graph Cut energy-minimization framework. We adapt the Graph Cut model to make it suitable for segmenting small, low-contrast structures, such as the caudate nucleus, by defining new energy function data and boundary potentials. In particular, we exploit information concerning the intensity and geometry, and we add supervised energies based on contextual brain structures. Furthermore, we reinforce boundary detection using a new multi-scale edgeness measure.

Results
We apply the novel CaudateCut method to the segmentation of the caudate nucleus to a new set of 39 pediatric attention-deficit/hyperactivity disorder (ADHD) patients and 40 control children, as well as to a public database of 18 subjects. We evaluate the quality of the segmentation using several volumetric and voxel by voxel measures. Our results show improved performance in terms of segmentation compared to state-of-the-art approaches, obtaining a mean overlap of 80.75%. Moreover, we present a quantitative volumetric analysis of caudate abnormalities in pediatric ADHD, the results of which show strong correlation with expert manual analysis.

Conclusion
CaudateCut generates segmentation results that are comparable to gold-standard segmentations and which are reliable in the analysis of differentiating neuroanatomical abnormalities between healthy controls and pediatric ADHD.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language (up) Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1475-925X ISBN Medium  
  Area Expedition Conference  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ ISH2011 Serial 1882  
Permanent link to this record
 

 
Author Mario Rojas; David Masip; A. Todorov; Jordi Vitria edit  url
doi  openurl
  Title Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models Type Journal Article
  Year 2011 Publication PloS one Abbreviated Journal Plos  
  Volume 6 Issue 8 Pages e23323  
  Keywords  
  Abstract JCR Impact Factor 2010: 4.411
Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions
 
  Address  
  Corporate Author Thesis  
  Publisher Public Library of Science Place of Publication Editor  
  Language (up) Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes OR;MV Approved no  
  Call Number Admin @ si @ RMT2011 Serial 1883  
Permanent link to this record
 

 
Author Miguel Angel Bautista; Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva edit  url
doi  isbn
openurl 
  Title On the Design of Low Redundancy Error-Correcting Output Codes Type Book Chapter
  Year 2011 Publication Ensembles in Machine Learning Applications Abbreviated Journal  
  Volume 373 Issue 2 Pages 21-38  
  Keywords  
  Abstract The classification of large number of object categories is a challenging trend in the Pattern Recognition field. In the literature, this is often addressed using an ensemble of classifiers . In this scope, the Error-Correcting Output Codes framework has demonstrated to be a powerful tool for combining classifiers. However, most of the state-of-the-art ECOC approaches use a linear or exponential number of classifiers, making the discrimination of a large number of classes unfeasible. In this paper, we explore and propose a compact design of ECOC in terms of the number of classifiers. Evolutionary computation is used for tuning the parameters of the classifiers and looking for the best compact ECOC code configuration. The results over several public UCI data sets and different multi-class Computer Vision problems show that the proposed methodology obtains comparable (even better) results than the state-of-the-art ECOC methodologies with far less number of dichotomizers.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language (up) Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1860-949X ISBN 978-3-642-22909-1 Medium  
  Area Expedition Conference  
  Notes MILAB; OR;HuPBA;MV Approved no  
  Call Number Admin @ si @ BEB2011b Serial 1886  
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Author Miguel Angel Bautista; Oriol Pujol; Xavier Baro; Sergio Escalera edit  url
isbn  openurl
  Title Introducing the Separability Matrix for Error Correcting Output Codes Coding Type Conference Article
  Year 2011 Publication 10th International Conference on Multiple Classifier Systems Abbreviated Journal  
  Volume 6713 Issue Pages 227-236  
  Keywords  
  Abstract Error Correcting Output Codes (ECOC) have demonstrate to be a powerful tool for treating multi-class problems. Nevertheless, predefined ECOC designs may not benefit from Error-correcting principles for particular multi-class data. In this paper, we introduce the Separability matrix as a tool to study and enhance designs for ECOC coding. In addition, a novel problem-dependent coding design based on the Separability matrix is tested over a wide set of challenging multi-class problems, obtaining very satisfactory results.  
  Address Napoles, Italy  
  Corporate Author Thesis  
  Publisher Springer-Verlag Berlin, Heidelberg Place of Publication Editor Carlo Sansone; Josef Kittler; Fabio Roli  
  Language (up) Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-21556-8 Medium  
  Area Expedition Conference MCS  
  Notes MILAB; OR;HuPBA;MV Approved no  
  Call Number Admin @ si @ BPB2011b Serial 1887  
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Author Ruth Aylett; Ginevra Castellano; Bogdan Raducanu; Ana Paiva; Marc Hanheide edit  url
doi  isbn
openurl 
  Title Long-term socially perceptive and interactive robot companions: challenges and future perspectives Type Conference Article
  Year 2011 Publication 13th International Conference on Multimodal Interaction Abbreviated Journal  
  Volume Issue Pages 323-326  
  Keywords human-robot interaction, multimodal interaction, social robotics  
  Abstract This paper gives a brief overview of the challenges for multi-model perception and generation applied to robot companions located in human social environments. It reviews the current position in both perception and generation and the immediate technical challenges and goes on to consider the extra issues raised by embodiment and social context. Finally, it briefly discusses the impact of systems that must function continually over months rather than just for a few hours.  
  Address Alicante  
  Corporate Author Thesis  
  Publisher ACM Place of Publication Editor  
  Language (up) Summary Language Original Title  
  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 OR;MV Approved no  
  Call Number Admin @ si @ ACR2011 Serial 1888  
Permanent link to this record
 

 
Author Antonio Hernandez; Carlos Primo; Sergio Escalera edit  doi
isbn  openurl
  Title Automatic user interaction correction via Multi-label Graph cuts Type Conference Article
  Year 2011 Publication In ICCV 2011 1st IEEE International Workshop on Human Interaction in Computer Vision HICV Abbreviated Journal  
  Volume Issue Pages 1276-1281  
  Keywords  
  Abstract Most applications in image segmentation requires from user interaction in order to achieve accurate results. However, user wants to achieve the desired segmentation accuracy reducing effort of manual labelling. In this work, we extend standard multi-label α-expansion Graph Cut algorithm so that it analyzes the interaction of the user in order to modify the object model and improve final segmentation of objects. The approach is inspired in the fact that fast user interactions may introduce some pixel errors confusing object and background. Our results with different degrees of user interaction and input errors show high performance of the proposed approach on a multi-label human limb segmentation problem compared with classical α-expansion algorithm.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language (up) Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-4673-0062-9 Medium  
  Area Expedition Conference HICV  
  Notes MILAB; HuPBA Approved no  
  Call Number Admin @ si @ HPE2011 Serial 1892  
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Author Miguel Reyes; Gabriel Dominguez; Sergio Escalera edit  url
doi  isbn
openurl 
  Title Feature Weighting in Dynamic Time Warping for Gesture Recognition in Depth Data Type Conference Article
  Year 2011 Publication 1st IEEE Workshop on Consumer Depth Cameras for Computer Vision Abbreviated Journal  
  Volume Issue Pages 1182-1188  
  Keywords  
  Abstract We present a gesture recognition approach for depth video data based on a novel Feature Weighting approach within the Dynamic Time Warping framework. Depth features from human joints are compared through video sequences using Dynamic Time Warping, and weights are assigned to features based on inter-intra class gesture variability. Feature Weighting in Dynamic Time Warping is then applied for recognizing begin-end of gestures in data sequences. The obtained results recognizing several gestures in depth data show high performance compared with classical Dynamic Time Warping approach.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language (up) Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-4673-0062-9 Medium  
  Area Expedition Conference CDC4CV  
  Notes HuPBA;MILAB Approved no  
  Call Number Admin @ si @ RDE2011 Serial 1893  
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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 (up) Summary Language Original Title  
  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 (up) Summary Language Original Title  
  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 (up) Summary Language Original Title  
  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  
Permanent link to this record
 

 
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 (up) Summary Language Original Title  
  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 (up) Summary Language Original Title  
  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 (up) Summary Language Original Title  
  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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