Facial Expression Recognition has become a hot research direction in human computer interaction, machine learning and image processing. However, the inaccuracy of facial expression similarity measure is always a key problem in facial expression classification. In order to solve this problem, a novel algorithm which is based on Discriminative Component Analysis algorithm, is proposed in this paper. Compared with Discriminative Component Analysis, our algorithm is based on maximizing within-class distance and minimizing between-class distance to choose chunklets, which guarantee the stability and accuracy of algorithm. The mean recognition rates are 80.42% and 95.71% under the condition of using hold-out method and leave-one-out method respectively. Experimental results show the effectiveness of our algorithm.
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