Wavelet networks for facial emotion recognition

Face emotion recognition is one of the most important and rapidly advanced active research areas of computer science. A new method for facial expression recognition based on wavelet network classifier is proposed in this paper. It allows us the detection of six basic emotions other than the neutral one: (Joy, surprise, sadness, anger, fear and disgust) The process is composed of three principle steps: face detection, features extraction and classification. The effectiveness of our proposed algorithm is experimentally demonstrated by using well-known test database: the extended cohen-kanade database.