Face detection using binary template matching and SVM

  • Authors:
  • Qiong Wang;Wankou Yang;Huan Wang;Jingyu Yang;Yujie Zheng

  • Affiliations:
  • School of Computer Science, Nanjing University of Science and Technology, Nanjing, China;School of Computer Science, Nanjing University of Science and Technology, Nanjing, China;School of Computer Science, Nanjing University of Science and Technology, Nanjing, China;School of Computer Science, Nanjing University of Science and Technology, Nanjing, China;School of Computer Science, Nanjing University of Science and Technology, Nanjing, China

  • Venue:
  • PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
  • Year:
  • 2006

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Abstract

This paper presents an efficient approach to achieve fast and accurate face detection in still gray level images. The structure of eye region is used as a robust cue to find possible eye pairs. Candidates of eye pair at different scales are discovered by finding regions which roughly match with the binary eye pair template. To obtain real ones, all the eye pair candidates are then verified by using SVM. Faces are finally located according to the eyes position. The proposed method is robust to deal with illumination changes, moderate rotations, glasses wearing and partial face occlusions. The proposed method is evaluated on the BioID face database. Comparative experimental results demonstrate its effectiveness.