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Robust sparse representation based face recognition in an adaptive weighted spatial pyramid structure

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Abstract

The sparse representation based classification methods has achieved significant performance in recent years. To fully exploit both the holistic and locality information of face samples, a series of sparse representation based methods in spatial pyramid structure have been proposed. However, there are still some limitations for these sparse representation methods in spatial pyramid structure. Firstly, all the spatial patches in these methods are directly aggregated with same weights, ignoring the differences of patches’ reliability. Secondly, all these methods are not quite robust to poses, expression and misalignment variations, especially in under-sampled cases. In this paper, a novel method named robust sparse representation based classification in an adaptive weighted spatial pyramid structure (RSRC-ASP) is proposed. RSRC-ASP builds a spatial pyramid structure for sparse representation based classification with a self-adaptive weighting strategy for residuals’ aggregation. In addition, three strategies, local-neighbourhood representation, local intra-class Bayesian residual criterion, and local auxiliary dictionary, are exploited to enhance the robustness of RSRC-ASP. Experiments on various data sets show that RSRC-ASP outperforms the classical sparse representation based classification methods especially for under-sampled face recognition problems.

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Acknowledgments

This work was supported by National Natural Science Foundation of China (Grant Nos. 61333015, 61302127, 11326198), China Postdoctoral Science Foundation (Grant No. 2015M570228), Opening Foundation of Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin Key Projects in the National Science and Technology Pillar Program (Grant No. 14ZCZDGX00033), and International Fostering Plan of Selected Excellent Postdoctors Subsidized by Tianjin City (2015). Thanks for the academic visiting support of the China Scholarship Council.

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Authors and Affiliations

  1. School of Electronics Engineering and Computer Science, Peking University, Beijing, 100871, China

    Xiao Ma, Fandong Zhang & Jufu Feng

  2. School of Computer Science and Software Engineering, Tianjin Polytechnic University, Tianjin, 300387, China

    Yuelong Li

  3. Department of Computer Science, University of York, York, YO10 5GH, UK

    Yuelong Li

Authors
  1. Xiao Ma
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  2. Fandong Zhang
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  3. Yuelong Li
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  4. Jufu Feng
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Correspondence to Xiao Ma.

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Ma, X., Zhang, F., Li, Y. et al. Robust sparse representation based face recognition in an adaptive weighted spatial pyramid structure. Sci. China Inf. Sci. 61, 012101 (2018). https://doi.org/10.1007/s11432-016-9009-6

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  • DOI: https://doi.org/10.1007/s11432-016-9009-6

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