Analizze And Research Of Facial Expression Recognition

Face plays an important part in people's interaction. So it is result in the modern world, face recognition automatically with computer is very important. In face facial expression is a critical part. Auto analyzes and recognition of facial expression make people deeply understanding human's sensation station and mechanism of human's cerebra, and enhanced the human-machine interaction. Improve computer's ability of feel environment, understanding sensation and intention and then response, so facial expression recognition plays an important in human-machine interaction. With the development of pattern recognitions in face recognition, use computer recognition expression is possible. The recognition and compose facial expression now is the hotspots research of pattern recognition and artificial intelligence. People devoted larger energy in this field, and find many methods for facial expression recognition.Now in face recognition field, Principle Component Analysis is widely used. This paper makes the research of PCA, find a PCA based method for facial expression recognition. This method is based of PCA, and used image process and neural network also. In image pre-process, use edge sharpening and distilling method. Pick up the outline of apparatus and expression texture, and wipe of the useless information .In the face feature extraction part; this paper used PCA, which can represent resource date in a lower dimensional space .In face recognition part, We have given the advantages and disadvantages of the BP algorithm, which has been widely used in pattern recognition, We also show how to design 3 layers BP network classifier and show how to make it more effective in face recognition, in this part we used genetic algorithm to optimize BP network.At last we discuss emphases and difficulty of above-all facial expression recognition methods, and put forward the future work development and direction.