Generalization of a vision-based computational model of mind-reading

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. © Springer-Verlag Berlin Heidelberg 2005.