Integrated person identification and expression recognition from facial images

In this paper we propose an integration of face identification and facial e xpression recognition. A face is modeled as a graph where the nodes represe nt facial feature points. This model is used for automatic face and facial feature point detection, and facial feature points tracked by applying flex ible feature matching. Face identification is performed by comparing tile g raphs representing the input fare image with individual face models. Facial expression is modeled by finding the relationship between the motion of fa cial feature points and expression change. Individual and average expressio n models are generated and then used to identify facial expressions under a ppropriate categories and the degree of expression changes. The expression model used for facial expression recognition is chosen by the results of fa ce identification.