Gabor-Eigen-Whiten-Cosine: a robust scheme for face recognition

Authors:
Weihong Deng;Jiani Hu;Jun Guo
Affiliations:
Beijing University of Posts and Telecommunications, Beijing, China;Beijing University of Posts and Telecommunications, Beijing, China;Beijing University of Posts and Telecommunications, Beijing, China
Venue:
AMFG'05 Proceedings of the Second international conference on Analysis and Modelling of Faces and Gestures
Year:
2005

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Abstract

Recognizing faces with complex intrapersonal variations is a challenging task, especially when using small size samples. Our approach, which obtains state of the art results, is based on a new face recognition scheme: Gabor-Eigen-Whiten-Cosine (GEWC). The novelty of this paper lies in 1) the finding that the same face with complex variations, projected into the Gabor based whitened PCA feature space, is approximately angle invariance; and 2) the experimental studies that analyze the joint contribution of Gabor wavelet, whitening process, and cosine similarity measure on the PCA based face recognition. The new GEWC method has been successfully tested and evaluated using comparative experiments on 3000+ FERET frontal face images with 1196 subjects. In particular, the GEWC method achieves constant 100% accuracy on the 200-subject experiment across illuminations and facial expressions. Furthermore, its recognition rates reach up to 96.3%, 99.5%, 78.8%, and 77.8% on the FB, fc, dup I, and dup II probes respectively using only one training sample per person.