An Illumination Invariant Face Recognition Method Based on Gradientfaces and 2DLDA

被引：0

作者：

Qi, Yongfeng ^{[1
]}

Huo, Yuanlian ^{[2
]}

机构：

[1] Northwest Normal Univ, Coll Comp Sci & Engn, Lanzhou 730070, Gansu, Peoples R China

[2] Northwest Normal Univ, Coll Phys & Elect Engn, Lanzhou 730070, Gansu, Peoples R China

来源：

PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INTELLIGENT COMMUNICATION | 2015年 / 16卷

关键词：

Gradientfaces; 2DLDA; face recognition; POSE;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Extracting illumination invariant features is an effective method to improve recognition rate of algorithm with varying illumination. In this paper, a novel illumination invariant method which combines Gradientface and 2DPDA is proposed. First, this approach transforms a face image into Gradientface, then the 2DPCA is used to reduce the dimension of Gradientface. The experimental results verify the effectiveness of our approach on CAS-PEAR-R1 and CMU PIE face databases.

引用

页码：422 / 424

页数：3

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