Facial expression recognition based on feature point vector and texture deformation energy parameters

Facial expression recognition is a popular and difficult research field in human-computer interaction. In order to remove effectively the differences in expression feature caused by individual differences, this paper firstly presents the feature point distance ratio coefficient based on feature point vector, and then gives the concept of texture deformation energy parameters. Finally, merges previously mentioned two parts to form a new expression feature for facial expression recognition. The proposed method is tested in the Cohn-Kanade database and the BHU facial expression database, and the experimental results show the recognition rates of the proposed method comparing with the existing ones increased by 4.5% and 3.9%.