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Author H.M.G. Stokman; Theo Gevers edit  openurl
  Title Selection and Fusion of Color Models for Image Feature Detection Type Journal
  Year 2007 Publication IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.29(3):371–381 Abbreviated Journal  
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  Notes ALTRES;ISE Approved no  
  Call Number Admin @ si @ StG2007 Serial 948  
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Author Joost Van de Weijer; Theo Gevers; A. Gijsenij edit  openurl
  Title Edge-Based Color Constancy Type Journal
  Year 2007 Publication IEEE Trans. on Image Processing, vol. 16(9):2207–2214 Abbreviated Journal  
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  Call Number CAT @ cat @ WGG2007 Serial 949  
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Author Mikhail Mozerov; Ariel Amato; Xavier Roca; Jordi Gonzalez edit  openurl
  Title Trajectory Occlusion Handling with Multiple View Distance Minimisation Clustering Type Journal
  Year 2008 Publication Optical Engineering, vol. 47(04)04702, DOI:10.11781.2909665 Abbreviated Journal  
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  Notes ISE Approved no  
  Call Number ISE @ ise @ MAR2008c Serial 970  
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Author Carles Fernandez; Xavier Roca; Jordi Gonzalez edit  openurl
  Title Providing Automatic Multilingual Text Generation to Artificial Cognitive Systems Type Journal
  Year 2008 Publication Abbreviated Journal  
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  Call Number ISE @ ise @ FRG2008 Serial 1021  
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Author Mikhail Mozerov; Ignasi Rius; Xavier Roca; Jordi Gonzalez edit   pdf
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  Title Nonlinear synchronization for automatic learning of 3D pose variability in human motion sequences Type Journal Article
  Year 2010 Publication EURASIP Journal on Advances in Signal Processing Abbreviated Journal EURASIPJ  
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  Abstract Article ID 507247
A dense matching algorithm that solves the problem of synchronizing prerecorded human motion sequences, which show different speeds and accelerations, is proposed. The approach is based on minimization of MRF energy and solves the problem by using Dynamic Programming. Additionally, an optimal sequence is automatically selected from the input dataset to be a time-scale pattern for all other sequences. The paper utilizes an action specific model which automatically learns the variability of 3D human postures observed in a set of training sequences. The model is trained using the public CMU motion capture dataset for the walking action, and a mean walking performance is automatically learnt. Additionally, statistics about the observed variability of the postures and motion direction are also computed at each time step. The synchronized motion sequences are used to learn a model of human motion for action recognition and full-body tracking purposes.		  
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  ISSN 1110-8657 ISBN Medium  
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  Notes ISE Approved no  
  Call Number ISE @ ise @ MRR2010 Serial 1208  
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