Improved elastic model matching algorithm for facial expression recognition

Key frames detected in Video stream contain sufficient expression information. In order to classify and recognize these expression information, a new elastic model matching algorithm is proposed in this paper. Firstly, expression template is transformed by Gabor wavelet, and the detection algorithm of the key expression in the template image is used. According to the feature information of the key expression, structure expression elastic graph, then by changing the key location in the expression template graph and doing non-rigid match of the expression template and expression elastic graph which is measured, so that similar degree between them is got. Finally, by improving the K-nearest neighbor classification strategy, the effective classification and recognition of measured image expression is achieved.