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Author M. Bressan; David Guillamet; Jordi Vitria edit  openurl
  Title (down) Using an ICA Representation of Local Color Histograms for Object Recognition Type Journal
  Year 2003 Publication Pattern Recognition, 36(3):691–701 (IF: 1.611) Abbreviated Journal  
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  Notes OR;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ BGV2003 Serial 365  
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Author Xavier Baro; Sergio Escalera; Jordi Vitria; Oriol Pujol; Petia Radeva edit  doi
openurl 
  Title (down) Traffic Sign Recognition Using Evolutionary Adaboost Detection and Forest-ECOC Classification Type Journal Article
  Year 2009 Publication IEEE Transactions on Intelligent Transportation Systems Abbreviated Journal TITS  
  Volume 10 Issue 1 Pages 113–126  
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  Abstract The high variability of sign appearance in uncontrolled environments has made the detection and classification of road signs a challenging problem in computer vision. In this paper, we introduce a novel approach for the detection and classification of traffic signs. Detection is based on a boosted detectors cascade, trained with a novel evolutionary version of Adaboost, which allows the use of large feature spaces. Classification is defined as a multiclass categorization problem. A battery of classifiers is trained to split classes in an Error-Correcting Output Code (ECOC) framework. We propose an ECOC design through a forest of optimal tree structures that are embedded in the ECOC matrix. The novel system offers high performance and better accuracy than the state-of-the-art strategies and is potentially better in terms of noise, affine deformation, partial occlusions, and reduced illumination.  
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  ISSN 1524-9050 ISBN Medium  
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  Notes OR;MILAB;HuPBA;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ BEV2008 Serial 1116  
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Author A. Pujol; Jordi Vitria; Felipe Lumbreras; Juan J. Villanueva edit  doi
openurl 
  Title (down) Topological principal component analysis for face encoding and recognition Type Journal Article
  Year 2001 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 22 Issue 6-7 Pages 769–776  
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  Abstract IF: 0.552  
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  Notes ADAS;OR;MV Approved no  
  Call Number ADAS @ adas @ PVL2001 Serial 155  
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Author Fadi Dornaika; Bogdan Raducanu edit  doi
openurl 
  Title (down) Three-Dimensional Face Pose Detection and Tracking Using Monocular Videos: Tool and Application Type Journal Article
  Year 2009 Publication IEEE Transactions on Systems, Man and Cybernetics part B Abbreviated Journal TSMCB  
  Volume 39 Issue 4 Pages 935–944  
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  Abstract Recently, we have proposed a real-time tracker that simultaneously tracks the 3-D head pose and facial actions in monocular video sequences that can be provided by low quality cameras. This paper has two main contributions. First, we propose an automatic 3-D face pose initialization scheme for the real-time tracker by adopting a 2-D face detector and an eigenface system. Second, we use the proposed methods-the initialization and tracking-for enhancing the human-machine interaction functionality of an AIBO robot. More precisely, we show how the orientation of the robot's camera (or any active vision system) can be controlled through the estimation of the user's head pose. Applications based on head-pose imitation such as telepresence, virtual reality, and video games can directly exploit the proposed techniques. Experiments on real videos confirm the robustness and usefulness of the proposed methods.  
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  Notes OR;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ DoR2009a Serial 1218  
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Author Bogdan Raducanu; Fadi Dornaika edit   pdf
doi  openurl
  Title (down) Texture-independent recognition of facial expressions in image snapshots and videos Type Journal Article
  Year 2013 Publication Machine Vision and Applications Abbreviated Journal MVA  
  Volume 24 Issue 4 Pages 811-820  
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  Abstract This paper addresses the static and dynamic recognition of basic facial expressions. It has two main contributions. First, we introduce a view- and texture-independent scheme that exploits facial action parameters estimated by an appearance-based 3D face tracker. We represent the learned facial actions associated with different facial expressions by time series. Second, we compare this dynamic scheme with a static one based on analyzing individual snapshots and show that the former performs better than the latter. We provide evaluations of performance using three subspace learning techniques: linear discriminant analysis, non-parametric discriminant analysis and support vector machines.  
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  Publisher Springer-Verlag Place of Publication Editor  
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  ISSN 0932-8092 ISBN Medium  
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  Notes OR; 600.046; 605.203;MV Approved no  
  Call Number Admin @ si @ RaD2013 Serial 2230  
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