Face detection using large margin classifiers

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, to 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.

• Type: Conference
• Year: 2001
• Where: ICIP
• Authors: Ming-Hsuan Yang, Dan Roth, Narendra Ahuja
• Keywords: Gray Scale Images, ICIP 2001, Image Processing, Large Margin Classifiers, Visual Learning Tasks