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A Fast Multi-Modal Approach to Facial Feature Detection
Breckenridge, Colorado January 05-January 07
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ACVMOT.2005.5Seventh IEEE Workshops on Application ...
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Chris Boehnen, University of Notre Dame, Sandia National Laboratories
Trina Russ, Sandia National Laboratories
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.
Citation:
Chris Boehnen, Trina Russ, "A Fast Multi-Modal Approach to Facial Feature Detection," wacv-motion, vol. 1, pp.135-142, Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1, 2005
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