Extraction of discriminative manifold for face recognition

Authors:
Yanmin Niu;Xuchu Wang
Affiliations:
College of Physics and Information Techniques, Chongqing Normal University, Chongqing, China;Key Lab on Opto-Electronic Technique and Systems, Ministry of Education, Chongqing University, Chongqing, China
Venue:
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
Year:
2006

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Abstract

It is very meaningful for dimension reduction by extraction and analysis of the underlying manifold embedded in face observation space, since the low dimensional manifold can represent the varying intrinsic features. However, this kind of manifold is perhaps not useful for face image recognition problem. This paper proposes a new discriminative manifold learning method which can efficiently discover the discriminative manifold. Besides the characteristic of preserving the local structure similarity in the face submanifold, the proposed method emphasizes the discriminative property of embedding much more throughout building and solving an object function. Experimental results on some open face datasets indicate the proposed method can achieve lower error rates.