Support Vector Machine Based Multi-View Face Detection and Pose Estimation
Yongmin Li ,
Shaogang Gong and
Heather
Liddell
- Introduction
- Relavant Publications
Introduction
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
-
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