Letters: Null space discriminant locality preserving projections for face recognition

Authors:
Liping Yang;Weiguo Gong;Xiaohua Gu;Weihong Li;Yixiong Liang
Affiliations:
Key Laboratory of Opto-Electronic Technology and Systems of Ministry of Education, Chongqing University, Chongqing 400030, China;Key Laboratory of Opto-Electronic Technology and Systems of Ministry of Education, Chongqing University, Chongqing 400030, China;Key Laboratory of Opto-Electronic Technology and Systems of Ministry of Education, Chongqing University, Chongqing 400030, China;Key Laboratory of Opto-Electronic Technology and Systems of Ministry of Education, Chongqing University, Chongqing 400030, China;School of Information Science and Engineering, Central South University, Hunan 410083, China
Venue:
Neurocomputing
Year:
2008

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Abstract

In this paper, we propose a null space discriminant locality preserving projections (NDLPP) method for facial feature extraction and recognition. Based on locality preserving projections (LPP) and discriminant locality preserving projections (DLPP) methods, NDLPP comes into the characteristics of DLPP that encodes both the geometrical and discriminant structure of the data manifold, and addresses the small sample size problem by solving an eigenvalue problem in null space. Experiments on synthetic data and ORL, Yale, and FERET face databases are performed to test and evaluate the proposed algorithm. The results demonstrate the effectiveness of NDLPP.