Review the Strength of Gabor Features for Face Recognition from the Angle of Its Robustness to Mis-Alignment

Authors:
Shiguang Shan;Wen Gao;Yizheng Chang;Bo Cao;Pang Yang
Affiliations:
Chinese Academy of Sciences, China;Chinese Academy of Sciences, China;Chinese Academy of Sciences, China;Chinese Academy of Sciences, China;Chinese Academy of Sciences, China
Venue:
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Year:
2004

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Abstract

Gabor feature has been widely recognized as better representation for face recognition in terms of rank-1 recognition rate. In this paper, we review the strength of Gabor feature for face recognition from the new angle of its robustness to mis-alignment using a novel quantificational evaluation method combining both the alignment precision and the recognition accuracy. Our experiments show that, compared with the gray-level intensity, Gabor feature is much more robust to image variation caused by the imprecision of facial feature localization, which further support the feasibility of Gabor representation.