A Random Network Ensemble for Face Recognition

  • Kwontaeg Choi
  • Kar-Ann Toh
  • Hyeran Byun
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5558)

Abstract

In this paper, we propose a random network ensemble for face recognition problem, particularly for images with a large appearance variation and with a limited number of training set. In order to reduce the correlation within the network ensemble using a single type of feature extractor and classifier, localized random facial features have been constructed together with internally randomized networks. The ensemble classifier is finally constructed by combining these multiple networks via a sum rule. The proposed method is shown to have a better accuracy(31.5% and 15.3% improvements on AR and EYALEB databases respectively) and a better efficiency than that of the widely used PCA-SVM.

Keywords

Face recognition random projection neural network 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Kwontaeg Choi
    • 1
  • Kar-Ann Toh
    • 2
  • Hyeran Byun
    • 1
  1. 1.Dept. of Computer ScienceYonsei UniversitySeoulSouth Korea
  2. 2.School of Electrical & Electronic EngineeringYonsei UniversitySeoulSouth Korea

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