A facial expression recognition strategy based on template matching

To solve the problems of lean, occlusion, and unbalance exposure, a new strategy of facial expression recognition based on template matching is proposed in the paper. The strategy firstly obtains the characteristics of half-facial expressions by using Gabor wavelet, and then calculates the picture´s Euclidean distance with the standard library; at last, classify expressions by using the method of K nearest neighbor. Experiments show that the strategy can improve the rate of facial expression recognition under the condition of without increasing in the expression library. The experiments prove that the Euclidean distance becomes small; and the amount of computing data reduces more.