关键词: 表情识别, 二维离散小波变换, 独立分量分析, 支持向量机

Abstract: An efficient facial expression recognition method by combining the two-dimensional Discrete Wavelet Transform（2D-DWT） method with the Independent Component Analysias（ICA） method are proposed.First，each image is decomposed into four sub-images by using the 2D-DWT approach，and then ICA approach is used to extract features form each sub-image respectively.Then，the differences of extracted features are obtained by subtracting features of neutral expression from the features of other expressions.All the differences of features are further combined and used for facial expression classification.Moreover，considering that the discriminative features extracted from each sub-image may not share the same metric scale measure，the authors also propose an effective features combination method in this paper.These experiment results indicate that the recognition ratios of facial expression are heightened by this method.

Key words: facial expression recognition, 2D Discrete Wavelet Transform, Independent Component Analysis, Support Vector Machine