Face Detection Using a Mixture of Factor Analyzers
Overview
We present a probabilistic method
to detect human faces using a mixture of factor analyzers.
One characteristic of this mixture
model is that it concurrently
performs clustering and, within each cluster,
local dimensionality reduction.
A wide range of face images that consists of faces in different poses,
faces in different expressions and faces under different lighting
conditions is used as the training set to capture the variations of
human faces.
In order to fit the mixture model to the sample face images,
the parameters are estimated using an EM algorithm.
Experimental results show that faces in different poses, with facial
expressions, and under different lighting conditions
are detected by our method.
Related Publications
- M.-H. Yang and N. Ahuja,
"Face Detection Using a Mixture of Factor Analyzers",
In Proceedings of the 1998 IEEE International Conference on Image Processing
(ICIP 99), Kobe, Japan, October, 1999.
Compressed postscript: icip99.ps.gz.
HTML: icip99.html.
Abstract: icip99-abstract.html.
- M.-H. Yang and N. Ahuja,
"Detecting Human Faces in Color Images",
In Proceedings of the 1998 IEEE International Conference on Image Processing
(ICIP 98), pp. 127-139,
Chicago, October, 1998.
Compressed postscript: icip98.ps.gz.
HTML: icip98.html.
Abstract: icip98-abstract.html.
- M.-H. Yang and N. Ahuja, "Gaussian Mixture Modeling of Human
Skin Color and Its Applications in Image and Video Databases",
In the 1999 SPIE/EI&T Storage and Retrieval for Image
and Video Databases, pp. 458-466, San Jose, January, 1999 .
Abstract: spie99-abstract.html.
Compressed postscript: spie99.ps.gz.
Training Images
Experimental Results
