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Face Recognition Using Null Space-Based Local Discriminant Embedding

  • Yanmin Niu
  • Xuchu Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4114)

Abstract

The manifold learning methods can discover the varying intrinsic features in face image space. However, in order to efficiently solve face image recognition problem with an image database, the extraction of discriminative features should be firstly considered. This paper proposes a new discriminative manifold learning method for face recognition. Besides like the recently proposed local perserving projectioin and local discriminative embedding algorithms which can preserve the local structure similarity in the face submanifold, our method emphasizes the discriminative property of embedding much more by a proposed Fisher Manifold Discriminant Embedding (Fisher MDE) criterion to build an object function and achieve the maximum. Experimental results on three open face datasets indicate the proposed method achieves lower error rates and provides a promising performance.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yanmin Niu
    • 1
  • Xuchu Wang
    • 2
  1. 1.College of Physics and Information Techniques, Chongqing Normal University, Chongqing 400047China
  2. 2.Key Lab on Opto-Electronic Technique and Systems, Ministry of Education, Chongqing University, Chongqing 400044China

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