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Combining Classifiers for Robust Face Detection

  • Lin-Lin Huang
  • Akinobu Shimizu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)

Abstract

In this paper, we propose a face detection method by combining classifiers. We apply two classifiers using features extracted from complementary feature subspaces learned by principal component analysis (PCA). The two classifiers employ the same classification model named a polynomial neural network (PNN). The outputs of the two classifiers are fused to make the final decision. The effectiveness of the proposed method has been demonstrated in experimentals.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Lin-Lin Huang
    • 1
  • Akinobu Shimizu
    • 2
  1. 1.Beijing University of Aeronautics and AstronauticsBeijingP.R. China
  2. 2.Tokyo University of Agriculture and TechnologyTokyoJapan

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