关键词: 表情识别, 特征提取, Gabor变换, 快速独立成分分析

Abstract: An effective method for the facial expression feature extraction is presented by combining the Gabor transform with the Fast Independent Component Analysis（FastICA）.Gabor wavelets exhibit strong characteristics of spatial locality and orientation selectivity，which are good for the extraction of the image’s texture.FastICA can reduce the redundancy of high-order statistics.The Gabor transform is carried out on each original image，and the outputs are concatenated into a Gabor feature vector.FastICA approach is used to extract features from the Gabor feature vectors of all the images.The K-neighbor method is used for classification.A series of experiments performed on the JAFFE database indicate the efficiency of the proposed method.

Key words: facial expression recognition, feature extraction, Gabor transform, fast independent component analysis