Expressional face image analysis with constrained optical flow

Face recognition is one of the most intensively studied topics in computer vision and pattern recognition. A constrained optical flow algorithm, which combines the advantages of the unambiguous correspondence of feature point labeling and the flexible representation of optical flow computation has been proposed in our pervious work. Facial expression normalization, from expressive to neutral facial images, based on optical flow analysis is discussed in this paper. In addition, we propose a new algorithm for nonnegative coefficient projection algorithm for projecting optical flow onto a facial expression subspace. Experimental validation is given to show that the proposed systems improve the accuracy of face and expression recognition on expressional face images.