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Parity symmetrical collaborative representation-based classification for face recognition

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Abstract

Although the subspace-based feature extraction algorithms provided a feasible strategy to deal with the classification of high-dimensional data, most of the existing algorithms are locality-oriented and suffer from many difficulties such as uncertain information associated with dataset and small sample size problem. In this paper, we propose a novel collaborative representation-based classification method using parity symmetry strategy for face recognition. More specifically, we firstly synthesize a set of parity symmetrical images by means of odd–even decomposition theorem, aiming to augment the training set. Secondly, each query sample is represented as a linear combination of the training samples from the extended training set, we then exploit the optimal representation of each reconstructed image with relevant contribution from each class. The final goal of the proposed method is to generate the best parity symmetrical representation of the query sample to perform robust face classification. Experimental results conducted on ORL, FERET, AR, PIE and LFW face databases demonstrate the effectiveness of the proposed method.

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Acknowledgments

The authors would like to thank the anonymous reviewers for their constructive advice. This work was supported by the Natural Science Foundation of China (Grant Nos. 61373055, 61471182, 61572242), the Natural Science Foundation of Jiangsu Province (Grant No. BK20130473) and the Fundamental Research Funds for the Central Universities (Grant Nos. JUSRP115A29, JUSRP51410B).

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Authors and Affiliations

  1. School of Internet of Things Engineering, Jiangnan University, Wuxi, 214122, China

    Xiaoning Song

  2. School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang, 212003, China

    Xibei Yang & Changbin Shao

  3. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China

    Jingyu Yang

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  1. Xiaoning Song
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  2. Xibei Yang
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  3. Changbin Shao
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  4. Jingyu Yang
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Correspondence to Xiaoning Song.

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Song, X., Yang, X., Shao, C. et al. Parity symmetrical collaborative representation-based classification for face recognition. Int. J. Mach. Learn. & Cyber. 8, 1485–1492 (2017). https://doi.org/10.1007/s13042-016-0520-4

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  • DOI: https://doi.org/10.1007/s13042-016-0520-4

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