Title
Quantifying interpersonal influence in face-to-face conversations based on visual attention patterns
Abstract
A novel measure for automatically quantifying the amount of interpersonal influence present in face-to-face conversations is proposed based on the visual-attention patterns of the participants as inferred from video sequences. First, we focus on the gaze of the participants as an indicator of addressing / listening behavior and build a probabilistic conversation model for inferring the gaze directions and conversation structures like monologue and dialogue, from observed utterances and head directions measured with image-based head trackers. Next, based on the estimates, the amount of influence is defined based on the amount of attention paid to speakers in monologues and to persons with whom the participants interact with during the dialogues. Experiments confirm that the proposed measures reveal some aspects of interpersonal influence in conversations.
Year
DOI
Venue
2006
10.1145/1125451.1125672
CHI Extended Abstracts
Keywords
Field
DocType
interpersonal influence present,interpersonal influence,novel measure,probabilistic conversation model,proposed measure,face-to-face conversation,image-based head tracker,participants interact,visual attention pattern,conversation structure,head direction,dynamic bayesian network,markov chain monte carlo,eye gaze
Conversation,Gaze,Computer science,Face-to-face,Active listening,Eye tracking,Human–computer interaction,Interpersonal influence,Probabilistic logic,Dynamic Bayesian network
Conference
ISBN
Citations 
PageRank 
1-59593-298-4
26
1.66
References 
Authors
7
4
Name
Order
Citations
PageRank
Kazuhiro Otsuka161954.15
Junji Yamato21120165.72
Yoshinao Takemae314813.42
Hiroshi Murase41927523.30