DocumentCode
2408716
Title
A subspace approach to face detection with support vector machines
Author
Ai, Haizhou ; Ying, Lihang ; Xu, Guangyou
Author_Institution
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
Volume
1
fYear
2002
fDate
2002
Firstpage
45
Abstract
We present a subspace approach to face detection with support vector machines (SVMs). A linear SVM classifier is trained as a filter to produce a subspace in which a non-linear SVM classifier with Gaussian kernel is trained for face detection. This makes training easier and results in a very efficient face detection algorithm. Experimental results demonstrate their promising performance compared with some well-known existing detectors.
Keywords
face recognition; image colour analysis; image segmentation; learning (artificial intelligence); learning automata; object detection; Gaussian kernel; face detection; filter; linear classifier; nonlinear classifier; subspace approach; support vector machines; Computer science; Detectors; Face detection; Gaussian processes; Kernel; Nonlinear filters; Skin; Statistical learning; Support vector machine classification; Support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2002. Proceedings. 16th International Conference on
ISSN
1051-4651
Print_ISBN
0-7695-1695-X
Type
conf
DOI
10.1109/ICPR.2002.1044585
Filename
1044585
Link To Document