Eigenface based Facial Expression Recognition

In this paper, the facial expression recognition system is described based on Eigenface. Facial expression recognition has become increasingly common in several applications in the fields of video conferences, surveillance, financial services, health treatment, and access control system. The performance of recognition depends mainly on several challenges. Lighting variations are also the most challenging in the recognition process. In this system, illumination invariant techniques applied for decreasing the lighting affected faces as a preprocessing stage. Eigen faces are used as feature extraction step. K-NN and Multi-SVMs classifier are used to identify the facial expression and to test the performance of the proposed system. The standard dataset of JAFFE is used in the experiments and 84.29% accuracy is achieved for facial expression recognition. The accuracy of the framework is contrasted with the state of the art methods tested on the JAFFE database.