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Automatic Two Phase Sparse Representation Method and Face Recognition Experiments

  • Conference paper
Biometric Recognition (CCBR 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8833))

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Abstract

The two phase sparse representation (TPSR) method has achieved promising face recognition performance. However, this method has the following flaw: its recognition accuracy varies with parameter M and at present there is no means to automatically set it. As a consequence, it becomes the bottleneck to apply the TPSR method to real-world problems. In this paper, we propose an improvement to TPSR (ITPSR), which can choose a proper value of parameter M for obtaining the optimal performance. Extensive experiments show that the proposed ITPSR is feasible and can obtain excellent performance.

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Author information

Authors and Affiliations

  1. Shenzhen Graduate School, Harbin Institute of Technology, China

    Ke Yan, Yong Xu & Jian Zhang

Authors
  1. Ke Yan
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  2. Yong Xu
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  3. Jian Zhang
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Editor information

Editors and Affiliations

  1. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, 100190, Beijing, China

    Zhenan Sun

  2. Institute of Computing Technology, Chinese Academy of Sciences, No.6 Kexueyuan South Road, P.O. Box 2704, 100190, HaiDian, Beijing, China

    Shiguang Shan

  3. School of Information Science and Engineering, Shenyang University of Technology, No.111, Shenliao West Road, Economic and Technological Development Zone, 110870, Shenyang, China

    Haifeng Sang  & Weiqi Yuan  & 

  4. Software Engineering Institute, Tsinghua University, No. 1 Tsinghua Yuan, Haidian District, 100084, Beijing, China

    Jie Zhou

  5. School of Computer Science and Engineering, Beihang University, No. 37 Xueyuan Road, Haidian District, 100191, Beijing, China

    Yunhong Wang

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© 2014 Springer International Publishing Switzerland

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Yan, K., Xu, Y., Zhang, J. (2014). Automatic Two Phase Sparse Representation Method and Face Recognition Experiments. In: Sun, Z., Shan, S., Sang, H., Zhou, J., Wang, Y., Yuan, W. (eds) Biometric Recognition. CCBR 2014. Lecture Notes in Computer Science, vol 8833. Springer, Cham. https://doi.org/10.1007/978-3-319-12484-1_2

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  • DOI: https://doi.org/10.1007/978-3-319-12484-1_2

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12483-4

  • Online ISBN: 978-3-319-12484-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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