Weighted joint sparse representation-based classification method for robust alignment-free face recognition

This work proposes a weighted joint sparse representation (WJSR)-based classification method for robust alignment-free face recognition, in which an image is represented by a set of scale-invariant feature transform descriptors. The proposed method considers the correlation and the reliability of th...

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Bibliographic Details
Published in:Journal of electronic imaging 2015-01, Vol.24 (1), p.013018-013018
Main Authors: Sun, Bo, Xu, Feng, Zhou, Guoyan, He, Jun, Ge, Fengxiang
Format: Article
Language:English
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Summary:This work proposes a weighted joint sparse representation (WJSR)-based classification method for robust alignment-free face recognition, in which an image is represented by a set of scale-invariant feature transform descriptors. The proposed method considers the correlation and the reliability of the query descriptors. The reliability is measured by the similarity information between the query descriptors and the atoms in the dictionary, which is incorporated into the l0∖l2-norm minimization to seek the optimal WJSR. Compared with the related state-of-art methods, the performance is advanced, as verified by the experiments on the benchmark face databases.
ISSN:1017-9909
1560-229X
DOI:10.1117/1.JEI.24.1.013018