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International Conference on Collaborative Computing: Networking, Applications and Worksharing

CollaborateCom 2018: Collaborative Computing: Networking, Applications and Worksharing pp 571–580Cite as

The Realization of Face Recognition Algorithm Based on Compressed Sensing (Short Paper)

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Abstract

Once the sparse representation-based classifier (SRC) was raised, it achieved a more outstanding performance than typical classification algorithm. Normally, SRC algorithm adopts \(l_1\)-norm minimization method to solve the sparse vector, and its computation complexity increases correspondingly. In this paper, we put forward a compressed sensing reconstruction algorithm based on residuals. This algorithm utilizes the local sparsity within figures as well as the non-local similarity among figure blocks to boost the performance of the reconstruction algorithm while remaining a median computation complexity. It achieves a superior recognition rate in the experiments of Yale facial database.

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References

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Author information

Authors and Affiliations

  1. University of Michigan, Ann Arbor, MI, 48105, USA

    Huimin Zhang

  2. Shanghai Jiao Tong University, Shanghai, 200240, China

    Huimin Zhang

  3. Jiangsu University, Zhenjiang, 212013, Jiangsu, China

    Yan Sun, Haiwei Sun & Xin Yuan

Authors
  1. Huimin Zhang
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  2. Yan Sun
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  3. Haiwei Sun
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  4. Xin Yuan
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Corresponding author

Correspondence to Huimin Zhang .

Editor information

Editors and Affiliations

  1. Shanghai University, Shanghai, China

    Honghao Gao

  2. University of West London, London, UK

    Xinheng Wang

  3. Hangzhou Dianzi University, Hangzhou Shi, Zhejiang, China

    Yuyu Yin

  4. London South Bank University, London, UK

    Muddesar Iqbal

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Cite this paper

Zhang, H., Sun, Y., Sun, H., Yuan, X. (2019). The Realization of Face Recognition Algorithm Based on Compressed Sensing (Short Paper). In: Gao, H., Wang, X., Yin, Y., Iqbal, M. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 268. Springer, Cham. https://doi.org/10.1007/978-3-030-12981-1_40

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  • DOI: https://doi.org/10.1007/978-3-030-12981-1_40

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-12980-4

  • Online ISBN: 978-3-030-12981-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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