Face detection using large margin classifiers

M. H. Yang, D. Roth, N. Ahuja

Research output: Contribution to conferencePaperpeer-review

4 Citations (Scopus)


Large margin classifiers have demonstrated their advantages in many visual learning tasks, and have attracted much attention in vision and image processing communities. In this paper we apply and compare two large margin classifiers, Support Vector Machines and Sparse Network of Winnows, so detect faces in still gray scale images. Furthermore, we study the theoretical frameworks of these classifiers and analyze the empirical results. Experiments on a test set of 24,045 images exhibit good generalization and robustness, and conform to theoretical analysis.

Original languageEnglish
Number of pages4
Publication statusPublished - 2001
EventIEEE International Conference on Image Processing (ICIP) - Thessaloniki, Greece
Duration: 2001 Oct 72001 Oct 10


OtherIEEE International Conference on Image Processing (ICIP)

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


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