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Proceedings Paper

Optimized sparse presentation-based classification method with weighted block and maximum likelihood model
Author(s): Jun He; Tian Zuo; Bo Sun; Xuewen Wu; Chao Chen
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Paper Abstract

This paper is aiming at applying sparse representation based classification (SRC) on face recognition with disguise or illumination variation. Having analyzed the characteristics of general object recognition and the principle of the classifier of SRC method, authors focus on evaluating blocks of a probe sample and propose an optimized SRC method based on position-preserving weighted block and maximum likelihood model. Principle and implementation of the proposed method have been introduced in the article, and experiments on Yale and AR face database have been given too. From experimental results, it can be seen that the proposed optimized SRC method works well than existing methods.

Paper Details

Date Published: 13 June 2014
PDF: 8 pages
Proc. SPIE 9090, Automatic Target Recognition XXIV, 909003 (13 June 2014); doi: 10.1117/12.2050374
Show Author Affiliations
Jun He, Beijing Normal Univ. (China)
Tian Zuo, Beijing Normal Univ. (China)
Bo Sun, Beijing Normal Univ. (China)
Xuewen Wu, Beijing Normal Univ. (China)
Chao Chen, Naval Academy of Armament (China)

Published in SPIE Proceedings Vol. 9090:
Automatic Target Recognition XXIV
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)

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