Extended Locality Preserving Discriminant Analysis for Face Recognition
Liping Yang, Weiguo Gong, Xiaohua Gu · 2010
In this paper, an extended locality preserving discriminant analysis (ELPDA) method is proposed. To address the disadvantages of original locality preserving discriminant analysis (LPDA), a new locality preserving between-class scatter, which is characterized by samples and the corresponding k out-class nearest neighbors, is defined. Moreover, the small sample size problem is also avoided by solving a new optimization function. Experimental results on AR and FERET subsets illustrate the effectiveness of the proposed method for face recognition.