A Subspace Approach to Face Detection with Support Vector Machines

  • Authors:
  • Haizhou Ai;Lihang Ying;Guangyou Xu

  • Affiliations:
  • -;-;-

  • Venue:
  • ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
  • Year:
  • 2002

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Abstract

We present a subspace approach to face detection with Support Vector Machine (SVMs). A linear SVM classifier is trained as a filter to produce a subspace in which a non-linear SVM classifier with Gaussian kernel is trained for face detection. This makes training easier and results in a very efficient face detection algorithm. Experimental results demonstrate their promising performance compared with some well-known existing detectors.