Social Signal Processing: Understanding Social Actions through nonverbal behaviour analysis

Vinciarelli, A. and Salamin, H. and Pantic, M. (2009) Social Signal Processing: Understanding Social Actions through nonverbal behaviour analysis. In: IEEE International Conference on Computer Vision and Pattern Recognition, CVPR '09, 20-25 June 2009, Miami, FL, USA.

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Abstract:	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.
Item Type:	Conference or Workshop Item
Copyright:	© 2009 IEEE
Faculty:	Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:	Human Media Interaction (HMI)
Link to this item:	http://purl.utwente.nl/publications/69562
Official URL:	http://dx.doi.org/10.1109/CVPR.2009.5204290
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