FACE RECOGNITION — A GENERALIZED MARGINAL FISHER ANALYSIS APPROACH
Dong Xu, Dacheng Tao, Xuelong Li, Shuicheng Yan · International Journal of Image and Graphics · 2007
In this paper, we propose a new supervised learning algorithm, which is named the Generalized Marginal Fisher Analysis (GMFA), to utilize the advantages of the Marginal Fisher Analysis (MFA) and the Generalized Singular Value Decomposition (GSVD) techniques for face recognition. The experimental results on several standard face databases demonstrate that GMFA outperforms LDA/Fisherface, LDA/GSVD and MFA.