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.
Original language | Undefined |
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Title of host publication | IEEE Computer Vision and Pattern Recognition Workshops, CVPRW 2011 |
Place of Publication | USA |
Publisher | IEEE |
Pages | 40-46 |
Number of pages | 7 |
ISBN (Print) | 978-1-4577-0529-8 |
DOIs | |
Publication status | Published - 12 Aug 2011 |
Event | 24th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011 - Colorado Springs, United States Duration: 20 Jun 2011 → 25 Jun 2011 Conference number: 24 |
Publication series
Name | |
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Publisher | IEEE Computer Society |
ISSN (Print) | 2160-7508 |
Conference
Conference | 24th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011 |
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Abbreviated title | CVPR 2011 |
Country/Territory | United States |
City | Colorado Springs |
Period | 20/06/11 → 25/06/11 |
Keywords
- METIS-279165
- IR-77954
- Multi-modal interaction
- Mimicry
- HMI-MI: MULTIMODAL INTERACTIONS
- EC Grant Agreement nr.: FP7/231287
- visual features
- human- human interaction
- EWI-20403