|
Published Articles >> Table of Contents >> Abstract
Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1
pp. 135-142
A Fast Multi-Modal Approach to Facial Feature Detection
Chris Boehnen, University of Notre Dame, Sandia National Laboratories
Trina Russ, Sandia National Laboratories
Full Article Text:
 
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ACVMOT.2005.5
Send link to a friend
| Abstract |
|
As interest in 3D face recognition increases the importance
of the initial alignment problem does as well. In this paper we
present a method utilizing the registered 2D color and range
image of a face to automatically identify the eyes, nose, and
mouth. These features are important to initially align faces in
both standard 2D and 3D face recognition algorithms. For our
algorithm to run as fast as possible, we focus on the 2D color
information. This allows the algorithm to run in approximately
4 seconds on a 640X480 image with registered range data. On a
database of 1,500 images the algorithm achieved a facial
feature detection rate of 99.6% with 0.4% of the images skipped
due to hair obstruction of the face.
|
 Additional Information
|
Citation:
Chris Boehnen, Trina Russ,
"A Fast Multi-Modal Approach to Facial Feature Detection,"
wacv-motion,
pp. 135-142,
Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1,
2005
|
|
