Abstract
This paper describes a vision-based computational model of mind-reading that infers complex mental states from head and facial expressions in real-time. The generalization ability of the system is evaluated on videos that were posed by lay people in a relatively uncontrolled recording environment for six mental states—agreeing, concentrating, disagreeing, interested, thinking and unsure. The results show that the system’s accuracy is comparable to that of humans on the same corpus.
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el Kaliouby, R., Robinson, P. (2005). Generalization of a Vision-Based Computational Model of Mind-Reading. In: Tao, J., Tan, T., Picard, R.W. (eds) Affective Computing and Intelligent Interaction. ACII 2005. Lecture Notes in Computer Science, vol 3784. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11573548_75
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DOI: https://doi.org/10.1007/11573548_75
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29621-8
Online ISBN: 978-3-540-32273-3
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