Support Vector Machine Based Multi-View Face Detection and Pose Estimation

Yongmin Li , Shaogang Gong and Heather Liddell
  1. Introduction
  2. Relavant Publications


A view-based Support Vector Machine (SVM) face model is presented in this work. Face detection is performed in the way of exhaustive scan. First pose is estimated using SVM regression. Then a piece-wise multi-view face model, which is comprised of a set of SVM-based classifiers on different views, is employed for face detection. Significant improvement in accuracy and reduction in computation are achieved since the pose information is explicitly used to select the appropriate classifier.

Relavant Publications

  1. Y. Li, S. Gong, and H. Liddell.
    Support vector regression and classification based multi-view face detection and recognition.
    In IEEE International Conference on Automatic Face & Gesture Recognition, pages 300-305, Grenoble, France, 2000.

Yongmin Li 2001-02-07