Dynamic Image Processing for Recognizing Motion of Emotional Expression

Abstract

A gesture plays an important role in emotional communication between human and robot. But conventional motion capture methods require special equipments and special markers to detect a locus of human's motion. In addition, the lack of data occurs frequently. In this paper, we focused on tracks of face and both hands based on Particle Filter. The likelihoods of face and hands are calculated based on distance and flesh color features, and applied to particle filter. Acutually, we reliably detected the locuses of nine representative emotional motions.