Bayesian face recognition using Gabor features

  • Authors:
  • Xiaogang Wang;Xiaoou Tang

  • Affiliations:
  • The Chinese University if Hong Kong, Shatin, Hong Kong;The Chinese University if Hong Kong, Shatin, Hong Kong

  • Venue:
  • WBMA '03 Proceedings of the 2003 ACM SIGMM workshop on Biometrics methods and applications
  • Year:
  • 2003

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Abstract

In this paper, we propose a new face recognition approach combining a Bayesian probabilistic model and Gabor filter responses. Since both the Bayesian algorithm and the Gabor features can reduce intrapersonal variation through different mechanisms, we integrate the two methods to take full advantage of both approaches. The efficacy of the new method is demonstrated by the experiments on 1180 face images from the XM2VTS database and 1260 face images from the AR database.