关键词: 支持向量机, 多分类器, 纠错输出编码, Gabor小波

Abstract: Multiple classification problems has been a hot topic in the field of pattern recognition. This paper proposes a multiple classifier algorithm based on Error-Correcting Output Coding（ECOC） and Support Vector Machine（SVM）. According to the communication coding theory to design error-correcting output coding matrix, it constructs some irrelevant SVMs, and integrates them as a multiple classifier. In order to verify the effectiveness of the classifier, using the Gabor wavelet to extract facial expression features, and application of two principal components（2DPCA） to reduce the dimension of extracted features, the classifier is used for facial expression recognition. Experimental results show that the method can effectively improve facial expression recognition and has excellent robustness.

Key words: Support Vector Machine（SVM）, multiple classifiers, Error-Correcting Output Coding（ECOC）, Gabor wavelet