MULTI-VIEW FACE RECOGNITION VIA JOINT DYNAMIC SPARSE REPRESENTATION

被引：0
|
作者：
Zhang, Haichao [1 ,2 ]
Nasrabadi, Nasser M. [3 ]
Huang, Thomas S. [2 ]
Zhang, Yanning [1 ]
机构：
[1] Northwestern Polytech Univ, Sch Comp Sci, Xian 710072, Peoples R China
[2] Univ Illinois, Beckman Inst, Chicago, IL 61801 USA
[3] US Army Lab, Adelphi, MD USA
来源：
2011 18TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | 2011年
关键词：
multi-view face recognition; joint dynamic sparsity; sparse representation based classification;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
We consider the problem of automatically recognizing a human face from its multi-view images with unconstrained poses and illuminations. We formulate the multi-view face recognition problem as that of classifying among several multi-input (views) regression models by using a novel joint dynamic sparse representation method which exploits jointly the inter-correlation among all the multi-view images in order to make a decision. Extensive experiments on CMU Multi-PIE face database are conducted to verify the efficacy of the proposed method.
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页数：4
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