THE SPARSE REPRESENTATION AND SMOOTHED L0 ALGORITHM FOR FACE RECOGNITION

被引：0
|
作者：
Zeng, Jun-Ying [1 ]
Zhai, Yi-Kui [1 ]
Gan, Jun-Ying [1 ]
机构：
[1] Wuyi Univ, Sch Informat Engn, Jiangmen 529020, Peoples R China
来源：
PROCEEDINGS OF 2015 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION (ICWAPR) | 2015年
关键词：
Face recognition; Sparse representation; l(0) norm;
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：
The sparse representation based classification (SRC) can effectively improve the face recognition rate. Smoothed l(0) algorithm has much faster calculation speed and requires fewer measured values than the other sparse representation method. In this paper, the sparse representation and smoothed l(0) algorithm for face recognition are presented to improve the face recognition under various conditions such as face disguise, illumination and pose changes, etc. The experiments on the AR, Extended Yale B and FERET face database verify the effectiveness of the presented method. The experimental results show that the face recognition algorithm increases to a certain extent in terms of recognition robustness and time than the original SRC.
引用
收藏
页码：34 / 38
页数：5
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