A robust face recognition method based on AdaBoost, EHMM and sample perturbation

  • Authors:

  • Yong Yang;Kan Tian;Zhengrong Chen

  • Affiliations:

  • Institute of Computer Science & Technology, Chongqing University of Posts and Telecommunications, Chongqing, P.R. China;Institute of Computer Science & Technology, Chongqing University of Posts and Telecommunications, Chongqing, P.R. China;Institute of Computer Science & Technology, Chongqing University of Posts and Telecommunications, Chongqing, P.R. China

  • Venue:
  • RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
  • Year:
  • 2011

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Abstract

Face recognition is a classical topic in pattern classification, although there are already some good methods and applications, robust face recognition methods are always pursued. In this paper, based on AdaBoost, embedded hidden Markov model(EHMM), and sample perturbation, a novel and robust face recognition method is proposed. Experiments results show that the proposed method can get higher recognition rate on benchmark datasets. Furthermore, the proposed method show robustness on the test samples with different illumination and shelter.