A Fusion Approach for Facial Expression Using Local Binary Pattern and a Pseudo 3D Face Model

The discovery of association between local facial feature and regional feature of image for recognizing facial expression is one of the current challenges in the regard of facial expression recognition. In this paper, we propose an approach fusing different complementary methods that can facilitate recognition of facial expression by exploring the knowledge on the face. The approach incorporates the joint work of Local Binary Pattern to extract the holistic facial area for recognizing facial expression. To deal with regional feature of face, a pseudo 3D face model is established for segmenting facial regions. Final, a propagation method is introduced to recognize the facial expression. Unlike many previous studies, the presented approach recognizes expressions from regional feature instead of holistic facial features or complete texture information. In order to validate our proposed approach, we have conducted experiments on the Extended Cohn-Kanade (CK+) facial expression database with an recognition rate of 91.7%.