Face Feature Extraction Based on Weighted Multiple Kernel Fisher Discriminant Analysis
基于多核Fisher判别分析的人脸特征提取

Kernel Fisher discriminant analysis method is an effective nonlinear discriminant analysis method. Tradition kernel Fisher discriminant analysis uses only single kernel function, which makes it insufficient in face feature extraction,therefore we proposed multiple kernel Fisher discriminant analysis. Weighted projections were obtained through weighted combination several projections obtained by single kernel Fisher discriminant,and then feature extraction and classification were made based on the weighted projections. Experimental results show that weighted multiple kernel Fisher discriminant analysis method is superior to single kernel Fisher discriminant analysis for facial feature extraction and classification.