Face Classification via Sparse Approximation

被引：0

作者：

Sonmez, Elena Battini ^{[1
]}

Sankur, Bulent ^{[2
]}

Albayrak, Songul ^{[3
]}

机构：

[1] Bilgi Univ, Dept Comp Sci, Istanbul, Turkey

[2] Bogazici Univ, Elect & Elect Engn Dept, TR-80815 Bebek, Turkey

[3] Yildiz Teknik Univ, Dept Comp Engn, Istanbul, Turkey

来源：

BIOMETRICS AND ID MANAGEMENT | 2011年 / 6583卷

关键词：

Face classification; sparse approximation; Fisher classifier; RECOGNITION; ROBUST; REPRESENTATION; ILLUMINATION;

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：

We address the problem of 2D face classification under adverse conditions. Faces are difficult to recognize since they are highly variable due to such factors as illumination, expression, pose, occlusion and resolution. We investigate the potential of a method where the face recognition problem is cast as a sparse approximation. The sparse approximation provides a significant amount of robustness beneficial in mitigating various adverse effects. The study is conducted experimentally using the Extended Yale Face B database and the results are compared against the Fisher classifier benchmark.

引用

页码：168 / +

页数：3

共 18 条

[1] Face recognition: The problem of compensating for changes in illumination direction [J].