Face Recognition under Varying Lighting Based on the Probabilistic Model of Gabor Phase

Authors:
Laiyun Qing;Shiguang Shan;Xilin Chen;Wen Gao
Affiliations:
Institute of Computing Technology, CAS, No.6 Kexueyuan South Road, Beijing, 100080, China;Graduate School, CAS, No.19, Yuquan Road,Beijing, 100039, China;Graduate School, CAS, No.19, Yuquan Road,Beijing, 100039, China;Graduate School, CAS, No.19, Yuquan Road,Beijing, 100039, China
Venue:
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Year:
2006

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Abstract

This paper present a novel method for robust illumination-tolerant face recognition based on the Gabor phase and a probabilistic similarity measure. Invited by the work in Eigenphases [1] by using the phase spectrum of face images, we use the phase information of the multi-resolution and multi-orientation Gabor filters. We show that the Gabor phase has more discriminative information and it is tolerate to illumination variations. Then we use a probabilistic similarity measure based on a Bayesian (MAP) analysis of the difference between the Gabor phases of two face images. We train the model using some images in the illumination subset of CMU-PIE database and test on the other images of CMU-PIE database and the Yale B database and get comparative results.