Proposed based on feature fusion and fuzzy kernel discriminant analysis (FKDA) facial expression recognition. First, face images of each piece of hand-set Bit 34 basis points, as the geometric features of facial expression images, while using Gabor wavelet transform method to transform the images of each piece of expression, and extraction-based Quasi-point of the Gabor wavelet coefficients, as Gabor features of facial expression image second, using canonical correlation analysis on the geometric features and Gabor features into Line feature fusion, as expression recognition of input features then, using fuzzy kernel discriminant analysis method to extract and further identification features of expression Finally, the most Neighbor classifier to complete expression of the classification. International expression by JAFFE database and Ekman "facial image" database on the experiment, confirmed The proposed method.

基于特征融合和模糊核判别分析的面部表情识别方法.pdf

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