Open AccessAutomatic dominance detection in dyadic conversations
Author(s) -
Sérgio Escalera,
Rosa María Goig Martínez,
Jordi Vitrià,
Petia Radeva,
M. Teresa Anguera
Publication year - 2010
Publication title -
escritos de psicología
Language(s) - English
Resource type - Journals
eISSN - 1989-3809
pISSN - 1138-2635
DOI - 10.24310/espsiescpsi.v3i2.13335
Subject(s) - categorization , dominance (genetics) , conversation , correlation , computer science , set (abstract data type) , natural language processing , artificial intelligence , psychology , cognitive psychology , social psychology , speech recognition , communication , mathematics , biochemistry , gene , chemistry , geometry , programming language
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.