关键词: 表情识别, 稀疏表示, Gabor滤波, 子空间

Abstract: A novel method to recognize facial expression in individual subspace using SRC（Sparse Representation based Classification） is proposed. Gabor filter is used to extract features of test expression image. The sparse representation coefficients of test image are gained by sparse decomposition. The individual subspace where test image lies in is found according to its sparse representation coefficients and its expression category is recognized in the subspace. The method eliminates preferably the disturbance of object without same identity to expression recognition. So recognition rates of expressions have been improved effectively. Experiments on the Cohn-Kanade face database and JAFFE face database show the proposed method achieves high performance to expression recognition.

Key words: expression recognition, sparse representation, Gabor filtering, subspace