Face Recognition Based on Two-dimensional Maximum Difference Marginal Fisher Analysis
基于最大差值的二维边界Fisher的人脸识别

A novel two-dimensional maximum difference marginal Fisher discriminant analysis(2DMDMFA) was proposed for face recognition.The algorithm adopts the difference of similarity matrix Sp which characterizes the interclass separability and similarity matrix Sc which characterizes the intraclass compactness as discriminant criterion.In such a way,the small sample size problem occurred in marginal Fisher analysis(MFA) is avoided.In addition,the construction of Sp and Sc is directly based on original training imag...