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Author Oriol Rodriguez-Leon; Josefina Mauri; Eduard Fernandez-Nofrerias; M.Gomez; Antonio Tovar; L.Cano; C.Diego; Carme Julia; Vicente del Valle; Debora Gil; Petia Radeva edit  openurl
  Title Ecografia Intracoronaria: Segmentacio Automatica de area de la llum Type Journal
  Year 2002 Publication Revista Societat Catalana de Cardiologia Abbreviated Journal  
  Volume 4 Issue 4 Pages (down) 42  
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  Address Barcelona  
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  Area Expedition Conference XIVe Congres de la Societat Catalana de Cardiologia  
  Notes MILAB;IAM Approved no  
  Call Number BCNPCL @ bcnpcl @ RMF2002 Serial 435  
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Author Sergio Escalera; R. M. Martinez; Jordi Vitria; Petia Radeva; Maria Teresa Anguera edit   pdf
openurl 
  Title Deteccion automatica de la dominancia en conversaciones diadicas Type Journal Article
  Year 2010 Publication Escritos de Psicologia Abbreviated Journal EP  
  Volume 3 Issue 2 Pages (down) 41–45  
  Keywords Dominance detection; Non-verbal communication; Visual features  
  Abstract Dominance is referred to the level of influence that a person has in a conversation. Dominance is an important research area in social psychology, but the problem of its automatic estimation is a very recent topic in the contexts of social and wearable computing. In this paper, we focus on the dominance detection of visual cues. We estimate the correlation among observers by categorizing the dominant people in a set of face-to-face conversations. Different dominance indicators from gestural communication are defined, manually annotated, and compared to the observers' opinion. Moreover, these indicators are automatically extracted from video sequences and learnt by using binary classifiers. Results from the three analyses showed a high correlation and allows the categorization of dominant people in public discussion video sequences.  
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  ISSN 1989-3809 ISBN Medium  
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  Notes HUPBA; OR; MILAB;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ EMV2010 Serial 1315  
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Author Oriol Rodriguez-Leon.A.Carol;H.Tizon; Eduard Fernandez-Nofrerias; Josefina Mauri; Vicente del Valle; Debora Gil; Aura Hernandez-Sabate; Petia Radeva edit  openurl
  Title Model estadístic-determinístic per la segmentació de l adventicia en imatges d ecografía intracoronaria Type Journal Article
  Year 2005 Publication Rev Societat Catalana Cardiologia Abbreviated Journal  
  Volume 5 Issue Pages (down) 41  
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  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ RCT2005 Serial 1637  
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Author Ole Larsen; Petia Radeva; Enric Marti edit   pdf
doi  openurl
  Title Bounds on the optimal elasticity parameters for a snake Type Journal Article
  Year 1995 Publication Image Analysis and Processing Abbreviated Journal  
  Volume Issue Pages (down) 37-42  
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  Abstract This paper develops a formalism by which an estimate for the upper and lower bounds for the elasticity parameters for a snake can be obtained. Objects different in size and shape give rise to different bounds. The bounds can be obtained based on an analysis of the shape of the object of interest. Experiments on synthetic images show a good correlation between the estimated behaviour of the snake and the one actually observed. Experiments on real X-ray images show that the parameters for optimal segmentation lie within the estimated bounds.  
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  Notes MILAB;IAM Approved no  
  Call Number IAM @ iam @ LRM1995a Serial 1559  
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Author Sergio Escalera; Oriol Pujol; J. Mauri; Petia Radeva edit  doi
openurl 
  Title Intravascular Ultrasound Tissue Characterization with Sub-class Error-Correcting Output Codes Type Journal Article
  Year 2009 Publication Journal of Signal Processing Systems Abbreviated Journal  
  Volume 55 Issue 1-3 Pages (down) 35–47  
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  Abstract Intravascular ultrasound (IVUS) represents a powerful imaging technique to explore coronary vessels and to study their morphology and histologic properties. In this paper, we characterize different tissues based on radial frequency, texture-based, and combined features. To deal with the classification of multiple tissues, we require the use of robust multi-class learning techniques. In this sense, error-correcting output codes (ECOC) show to robustly combine binary classifiers to solve multi-class problems. In this context, we propose a strategy to model multi-class classification tasks using sub-classes information in the ECOC framework. The new strategy splits the classes into different sub-sets according to the applied base classifier. Complex IVUS data sets containing overlapping data are learnt by splitting the original set of classes into sub-classes, and embedding the binary problems in a problem-dependent ECOC design. The method automatically characterizes different tissues, showing performance improvements over the state-of-the-art ECOC techniques for different base classifiers. Furthermore, the combination of RF and texture-based features also shows improvements over the state-of-the-art approaches.  
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  ISSN 1939-8018 ISBN Medium  
  Area Expedition Conference  
  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ EPM2009 Serial 1258  
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