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Facial expression imitation in human robot interaction

In this paper, we propose an interactive system for reconstructing human facial expression. In the system, a nonlinear mass-spring model is employed to simulate twenty two facial musclespsila tensions during facial expressions, and then the elastic forces of these tensions are grouped into a vector which is used as the input for facial expression recognition. The experimental results show that the nonlinear facial mass-spring model coupled with the SVM classifier is effective to recognize the facial expressions. Finally, we introduce our robot that can make artificial facial expressions. Experimental results of facial expression generation demonstrate that our robot can imitate six types of facial expressions.