Neighborhood preserving fisher discriminant analysis

被引：1

作者：

Wang G. ^{[1
]}

Zhang W. ^{[1
]}

机构：

[1] Department of Computer and Information Engineering, Luoyang Institute of Science and Technology, 471023 Luoyang, Henan

来源：

Information Technology Journal | 2011年 / 10卷 / 12期

关键词：

Face recognition; Fisher criterion; Neighborhood preserving projections; Schur-decomposition; Subspace learning;

D O I：

10.3923/itj.2011.2464.2469

中图分类号：

学科分类号：

摘要：

In this study, a novel subspace learning method named Neighborhood Preserving Fisher Discriminant Analysis (NPFDA) is proposed for face recognition. Based on Fisher Discriminant Analysis (FDA), NPFDA takes into account the local geometry structure information, changes the objective function. Thus, two abilities of manifold learning and classification are combined into the proposed method. In order to improve the discriminating power, Schur-decomposition is used to get the orthogonal basis vectors. Experimental results on the Yale face database and Feret face database demonstrate the effectiveness of the proposed method. © 2011 Asian Network for Scientific Information.

引用

页码：2464 / 2469

页数：5

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