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Two-stage sparse representation-based face recognition with reconstructed images

[+] Author Affiliations
Guangtao Cheng

Tianjin University, School of Electronic Information Engineering, Tianjin 30072, China

North China Institute of Aerospace Engineering, Department of Foundation Science, Langfang 065000, China

Zhanjie Song

Tianjin University, School of Science, Tianjin 30072, China

Yang Lei

Tianjin University, School of Electronic Information Engineering, Tianjin 30072, China

Xiuning Han

Tianjin University, School of Science, Tianjin 30072, China

J. Electron. Imaging. 23(5), 053021 (Oct 15, 2014). doi:10.1117/1.JEI.23.5.053021
History: Received June 20, 2014; Revised September 10, 2014; Accepted September 15, 2014
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Abstract.  In order to address the challenges that both the training and testing images are contaminated by random pixels corruption, occlusion, and disguise, a robust face recognition algorithm based on two-stage sparse representation is proposed. Specifically, noises in the training images are first eliminated by low-rank matrix recovery. Then, by exploiting the first-stage sparse representation computed by solving a new extended 1-minimization problem, noises in the testing image can be successfully removed. After the elimination, feature extraction techniques that are more discriminative but are sensitive to noise can be effectively performed on the reconstructed clean images, and the final classification is accomplished by utilizing the second-stage sparse representation obtained by solving the reduced 1-minimization problem in a low-dimensional feature space. Extensive experiments are conducted on publicly available databases to verify the superiority and robustness of our algorithm.

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Citation

Guangtao Cheng ; Zhanjie Song ; Yang Lei and Xiuning Han
"Two-stage sparse representation-based face recognition with reconstructed images", J. Electron. Imaging. 23(5), 053021 (Oct 15, 2014). ; http://dx.doi.org/10.1117/1.JEI.23.5.053021


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