tailieunhanh - Báo cáo sinh học: " Research Article Automatic Detection of Dominance and Expected Interest"

Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học Journal of Biology đề tài:Research Article Automatic Detection of Dominance and Expected Interest | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID491819 12 pages doi 2010 491819 Research Article Automatic Detection of Dominance and Expected Interest Sergio Escalera 1 2 Oriol Pujol 1 2 Petia Radeva 1 2 Jordi Vitria 1 2 and M. Teresa Anguera3 1 Computer Vision Center Campus UAB Edifici O 08193 Bellaterra Spain 2Departament de Matematica Aplicada i Analisi Universitat de Barcelona Gran Via de les Corts Catalanes 585 08007 Barcelona Spain 3Departament de Metodologia de les Ciencies del Comportament Universitat de Barcelona Gran Via de les Corts Catalanes 585 08007 Barcelona Spain Correspondence should be addressed to Sergio Escalera sescalera@ Received 3 August 2009 Revised 24 December 2009 Accepted 17 March 2010 Academic Editor Satya Dharanipragada Copyright 2010 Sergio Escalera et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 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 .