Abstract：Gabor features are successfully applied to solve the problems of facial expression recognition. However, the dimension of Gabor features is usually too high to be practically applicable. A method based on Pyramid Histogram of Oriented Gradients (PHOG) feature and Clustering Linear Discriminate Analysis (CLDA) is proposed for smile expression recognition. The main merits of the proposed system are that the complexity can be decreased with low-dimension PHOG feature, and the multi-model problem can be overcome by CLDA. The experimental results show that system with PHOG feature achieves competitive or even higher recognition accuracy than with the Gabor feature, but with much lower of computation time cost. Moreover, the performance of CLDA does not be degraded significantly when decreasing the feature dimension.
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2012, Vol. 25 
