Generalized Weber-face for illumination-robust face recognition

被引：51
|
作者：
Wu, Yong [1 ,2 ]
Jiang, Yinyan [1 ,2 ]
Zhou, Yicong [3 ]
Li, Weifeng [1 ,2 ]
Lu, Zongqing [1 ,2 ]
Liao, Qingmin [1 ,2 ]
机构：
[1] Tsinghua Univ, Grad Sch Shenzhen, Dept Elect Engn, Beijing, Peoples R China
[2] Shenzhen Key Lab Informat Sci & Technol, Guangzhou, Guangdong, Peoples R China
[3] Univ Macau, Dept Comp & Informat Sci, Macau, Peoples R China
来源：
NEUROCOMPUTING | 2014年 / 136卷
关键词：
Face recognition; Illumination insensitive representation; Weber-face; Multi-scale information; IMAGE;
D O I：
10.1016/j.neucom.2014.01.006
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Robust face recognition under uncontrolled illumination conditions is one of the key challenges for real-time face recognition systems. Weber-face (WF) is an illumination insensitive face representation based on Weber' law. In this letter, we develop a generalized Weber-face (GWF) which extracts the statistics of multi-scale information from face images. By assigning different weights to the inner-ground and outer-ground we further develop a weighted GWF (wGWF) version. Based on our experiments on the extended Yale-B and FERET face database we show that the proposed methods are robust to illumination variations and can obtain promising performance comparable with existing approaches. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码：262 / 267
页数：6
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