Face Recognition - a Generalized Marginal Fisher Analysis Approach
نویسندگان
چکیده
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.
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عنوان ژورنال:
- Int. J. Image Graphics
دوره 7 شماره
صفحات -
تاریخ انتشار 2007