Facial expression recognition using geometric and appearance features

A novel method using hybrid geometric and appearance features of the difference between the neutral and fully expressive facial expression images is proposed for facial expression recognition in this paper. The difference tends to emphasize the facial parts that are changed from the neutral to expressive face and eliminate in that way the identity of the facial image. The hybrid features include facial feature point displacements and local texture differences between the normalized neutral and expressive facial expression images. The proposed method achieved an average accuracy of 95% in the extended Cohn-Kanade database with a Support Vector Machine (SVM) classification method.