Abstract
Deception dectection is one of the most difficult problems in affect recognition and expression research area. Recently, non-verbal methods of detecting deception have appeared to be promising. Thomas[1] presented a proof-of-concept study based on the blob analysis of some suspects’ interviews and mock experiments video clips. In this paper, we present our recent research work in the direction of developing an automated deception detection system. We propose a blob motion pattern analysis approach to solve this problem.
Supported by the National Natural Science Foundation of China (60433030).
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Mafia game introduction, http://en.wikipedia.org/wiki/Mafia_Game.htm
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© 2007 Springer-Verlag Berlin Heidelberg
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Xia, F., Wang, H., Huang, J. (2007). Deception Detection Via Blob Motion Pattern Analysis. In: Paiva, A.C.R., Prada, R., Picard, R.W. (eds) Affective Computing and Intelligent Interaction. ACII 2007. Lecture Notes in Computer Science, vol 4738. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74889-2_70
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DOI: https://doi.org/10.1007/978-3-540-74889-2_70
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74888-5
Online ISBN: 978-3-540-74889-2
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