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Improvement on Null Space LDA for Face Recognition: A Symmetry Consideration

  • Wangmeng Zuo
  • Kuanquan Wang
  • David Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3832)

Abstract

The approximate bilateral symmetry of human face has been explored to improve the recognition performance of some face recognition algorithms such as Linear Discriminant Analysis (LDA) and Direct-LDA (D-LDA). In this paper we summary the ways to generate virtual sample using facial symmetry, and investigate the three strategies of using facial symmetric information in the Null Space LDA (NLDA) framework. The results of our experiments indicate that, the use of facial symmetric information can further improve the recognition accuracy of conventional NLDA.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Wangmeng Zuo
    • 1
  • Kuanquan Wang
    • 1
  • David Zhang
    • 2
  1. 1.School of Computer Science and TechnologyHarbin Institute of TechnologyHarbinChina
  2. 2.Biometrics Research Centre, Department of ComputingThe Hong Kong Polytechnic UniversityKowloon, Hong Kong

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