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Author O. Rodriguez-Leor; Carlo Gatta; E Fernandez-Nofrerias; Oriol Pujol; Neus Salvatella; C. Bosch; H. Tizon; Petia Radeva; J. Mauri edit  openurl
  Title Computationally Efficient Image-based IVUS Pullbacks Gating Type Journal
  Year 2008 Publication European Heart Journal, ESC Supplement, Munich, 2008, p. 775 Abbreviated Journal  
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  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ RGF2008 Serial 1036  
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Author Sergio Escalera; Oriol Pujol; Petia Radeva; Jordi Vitria; Maria Teresa Anguera edit  doi
openurl 
  Title Automatic Detection of Dominance and Expected Interest Type Journal Article
  Year 2010 Publication EURASIP Journal on Advances in Signal Processing Abbreviated Journal EURASIPJ  
  Volume (up) Issue Pages 12  
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  Abstract Article ID 491819
Social Signal Processing is an emergent area of research that focuses on the analysis of social constructs. Dominance and interest are two of these social constructs. Dominance refers to the level of influence a person has in a conversation. Interest, when referred in terms of group interactions, can be defined as the degree of engagement that the members of a group collectively display during their interaction. In this paper, we argue that only using behavioral motion information, we are able to predict the interest of observers when looking at face-to-face interactions as well as the dominant people. First, we propose a simple set of movement-based features from body, face, and mouth activity in order to define a higher set of interaction indicators. The considered indicators are manually annotated by observers. Based on the opinions obtained, we define an automatic binary dominance detection problem and a multiclass interest quantification problem. Error-Correcting Output Codes framework is used to learn to rank the perceived observer's interest in face-to-face interactions meanwhile Adaboost is used to solve the dominant detection problem. The automatic system shows good correlation between the automatic categorization results and the manual ranking made by the observers in both dominance and interest detection problems.
 
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  ISSN 1110-8657 ISBN Medium  
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  Notes OR;MILAB;HUPBA;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ EPR2010d Serial 1283  
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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 (up) Issue Pages 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 Oriol Rodriguez-Leon; Josefina Mauri;Eduard Fernandez-Nofrerias; C.Garcia; R.Villuendas; Vicente del Valle; Debora Gil;Petia Radeva edit  openurl
  Title Reconstruction of a spatio-temporal model of the intima layer from intravascular ultrasound sequences Type Journal Article
  Year 2003 Publication European Heart Journal Abbreviated Journal  
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  Area Expedition Conference ESC Congress  
  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ RMF2003c Serial 1641  
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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 (up) 3 Issue 2 Pages 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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