Abstract
| Original language | Undefined |
|---|---|
| Title of host publication | IEEE International Conference on Computer Vision and Pattern Recognition (CVPR'09) |
| Place of Publication | Los Alamitos |
| Publisher | IEEE Computer Society |
| Pages | 42-49 |
| Number of pages | 8 |
| ISBN (Print) | 978-1-4244-3994-2 |
| DOIs | |
| Publication status | Published - 18 Aug 2009 |
Publication series
| Name | |
|---|---|
| Publisher | IEEE Computer Society Press |
| Volume | 3 |
Keywords
- METIS-264327
- Body posture
- IR-69562
- Nonverbal Behavior Analysis
- Facial Expression
- HMI-HF: Human Factors
- EC Grant Agreement nr.: FP7/231287
- social interactions
- machine detectable evidence
- Social Signal Processing
- HMI-MI: MULTIMODAL INTERACTIONS
- EWI-17216
Cite this
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Social Signal Processing: Understanding Social Actions through nonverbal behaviour analysis. / Vinciarelli, A.; Salamin, H.; Pantic, Maja.
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR'09). Los Alamitos : IEEE Computer Society, 2009. p. 42-49 10.1109/CVPR.2009.5204290.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - Social Signal Processing: Understanding Social Actions through nonverbal behaviour analysis
AU - Vinciarelli, A.
AU - Salamin, H.
AU - Pantic, Maja
N1 - 10.1109/CVPR.2009.5204290
PY - 2009/8/18
Y1 - 2009/8/18
N2 - This paper introduces social signal processing (SSP), the domain aimed at automatic understanding of social interactions through analysis of nonverbal behavior. The core idea of SSP is that nonverbal behavior is machine detectable evidence of social signals, the relational attitudes exchanged between interacting individuals. Social signals include (dis-)agreement, empathy, hostility, and any other attitude towards others that is expressed not only by words but by nonverbal behaviors such as facial expression and body posture as well. Thus, nonverbal behavior analysis is used as a key to automatic understanding of social interactions. This paper presents not only a survey of the related literature and the main concepts underlying SSP, but also an illustrative example of how such concepts are applied to the analysis of conflicts in competitive discussions.
AB - This paper introduces social signal processing (SSP), the domain aimed at automatic understanding of social interactions through analysis of nonverbal behavior. The core idea of SSP is that nonverbal behavior is machine detectable evidence of social signals, the relational attitudes exchanged between interacting individuals. Social signals include (dis-)agreement, empathy, hostility, and any other attitude towards others that is expressed not only by words but by nonverbal behaviors such as facial expression and body posture as well. Thus, nonverbal behavior analysis is used as a key to automatic understanding of social interactions. This paper presents not only a survey of the related literature and the main concepts underlying SSP, but also an illustrative example of how such concepts are applied to the analysis of conflicts in competitive discussions.
KW - METIS-264327
KW - Body posture
KW - IR-69562
KW - Nonverbal Behavior Analysis
KW - Facial Expression
KW - HMI-HF: Human Factors
KW - EC Grant Agreement nr.: FP7/231287
KW - social interactions
KW - machine detectable evidence
KW - Social Signal Processing
KW - HMI-MI: MULTIMODAL INTERACTIONS
KW - EWI-17216
U2 - 10.1109/CVPR.2009.5204290
DO - 10.1109/CVPR.2009.5204290
M3 - Conference contribution
SN - 978-1-4244-3994-2
SP - 42
EP - 49
BT - IEEE International Conference on Computer Vision and Pattern Recognition (CVPR'09)
PB - IEEE Computer Society
CY - Los Alamitos
ER -