TY - GEN
T1 - Part-based face recognition using near infrared images
AU - Pan, Ke
AU - Liao, Shengcai
AU - Zhang, Zhijian
AU - Li, Stan Z.
AU - Zhang, Peiren
PY - 2007
Y1 - 2007
N2 - Recently, we developed NIR based face recognition for highly accurate face recognition under illumination variations [10]. In this paper, we present a part-based method for improving its robustness with respect to pose variations. An NIR face is decomposed into parts. A part classifier is built for each part, using the most discriminative LBP histogram features selected byAdaBoost learning. The outputs of part classifiers are fused to give the final score. Experiments show that the present method outperforms the whole face-based method [10] by 4.53%.
AB - Recently, we developed NIR based face recognition for highly accurate face recognition under illumination variations [10]. In this paper, we present a part-based method for improving its robustness with respect to pose variations. An NIR face is decomposed into parts. A part classifier is built for each part, using the most discriminative LBP histogram features selected byAdaBoost learning. The outputs of part classifiers are fused to give the final score. Experiments show that the present method outperforms the whole face-based method [10] by 4.53%.
UR - http://www.scopus.com/inward/record.url?scp=35148850161&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=35148850161&partnerID=8YFLogxK
U2 - 10.1109/CVPR.2007.383459
DO - 10.1109/CVPR.2007.383459
M3 - Conference contribution
AN - SCOPUS:35148850161
SN - 1424411807
SN - 9781424411801
T3 - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
BT - 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07
T2 - 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07
Y2 - 17 June 2007 through 22 June 2007
ER -