Part-based face recognition using near infrared images

被引：0

作者：

Pan, Ke ^{[1
]}

Liao, Shengcai ^{[2
]}

Zhang, Zhijian ^{[1
]}

Li, Stan Z. ^{[2
]}

Zhang, Peiren ^{[1
]}

机构：

[1] Univ Sci & Technol China, Hefei 230026, Peoples R China

[2] Chinese Acad Sci, Inst Automat, Ctrr Biomet & Secur Res & Nat Lab Pattern Recogni, Beijing 100080, Peoples R China

来源：

2007 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOLS 1-8 | 2007年

关键词：

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

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 by AdaBoost 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%.

引用

页码：3494 / +

页数：2

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