DocumentCode
2722101
Title
Automatic visual mimicry expression analysis in interpersonal interaction
Author
Sun, Xiaofan ; Truong, Khiet P. ; Nijholt, Anton ; Pantic, Maja
Author_Institution
Human Media Interaction, Univ. of Twente, Enschede, Netherlands
fYear
2011
fDate
20-25 June 2011
Firstpage
40
Lastpage
46
Abstract
Mimicry occurs in conversations both when people agree with each other and when they do not. However, it has been reported that there is more mimicry when people agree than when they disagree: when people want to express shared opinions and attitudes, they do so by displaying behavior that is similar to their interlocutors´ behavior. In a conversation, mimicry occurs in order to gain acceptance from an interaction partner by conforming to that person´s attitudes, opinions, and behavior. In this paper we describe how visual behavioral information expressed between two interlocutors can be used to detect and identify visual mimicry. We extract and encode visual features that are expected to represent mimicry in a useful way. In order to show that mimicry has indeed occurred, we calculate correlations between visual features extracted from the interactants and compare these against each other and against a baseline. We show that it is possible to visualize the occurrence of visual mimicry during the progress of a conversation which allows us to research in which situations and to what extent mimicry occurs.
Keywords
behavioural sciences computing; emotion recognition; feature extraction; automatic visual mimicry expression analysis; behavior display; feature extraction; interaction partner; interpersonal interaction; Cameras; Correlation; Feature extraction; Histograms; Humans; MIMICs; Visualization;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition Workshops (CVPRW), 2011 IEEE Computer Society Conference on
Conference_Location
Colorado Springs, CO
ISSN
2160-7508
Print_ISBN
978-1-4577-0529-8
Type
conf
DOI
10.1109/CVPRW.2011.5981812
Filename
5981812
Link To Document