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Chinese Conference on Biometric Recognition

CCBR 2017: Biometric Recognition pp 474–483Cite as

Pose-Based Temporal-Spatial Network (PTSN) for Gait Recognition with Carrying and Clothing Variations

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10568))

Abstract

One of the most attractive biometric techniques is gait recognition, since its potential for human identification at a distance. But gait recognition is still challenging in real applications due to the effect of many variations on the appearance and shape. Usually, appearance-based methods need to compute gait energy image (GEI) which is extracted from the human silhouettes. GEI is an image that is obtained by averaging the silhouettes and as result the temporal information is removed. The body joints are invariant to changing clothing and carrying conditions. We propose a novel pose-based gait recognition approach that is more robust to the clothing and carrying variations. At the same time, a pose-based temporal-spatial network (PTSN) is proposed to extract the temporal-spatial features, which effectively improve the performance of gait recognition. Experiments evaluated on the challenging CASIA B dataset, show that our method achieves state-of-the-art performance in both carrying and clothing conditions.

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Acknowledgments

The work is supported by the Science Foundation of Shenzhen (Grant No. JCYJ20150324141711699).

Author information

Authors and Affiliations

  1. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, 518060, China

    Rijun Liao & Shiqi Yu

  2. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Chunshui Cao & Yongzhen Huang

  3. Advanced Technologies Application Center (CENATAV), 7ma A 21406, Playa, Havana, Cuba

    Edel B. Garcia

Authors
  1. Rijun Liao
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  2. Chunshui Cao
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  3. Edel B. Garcia
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  4. Shiqi Yu
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  5. Yongzhen Huang
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Corresponding author

Correspondence to Shiqi Yu .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Jie Zhou

  2. Beihang University, Beijing, China

    Yunhong Wang

  3. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Zhenan Sun

  4. Computing and Technology, Chinese Academy of Sciences, Beijing, China

    Yong Xu

  5. Shenzhen University, Shenzhen, China

    Linlin Shen

  6. Tsinghua University, Beijing, China

    Jianjiang Feng

  7. Chinese Academy of Sciences, Beijing, China

    Shiguang Shan

  8. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Yu Qiao

  9. Graduate School at Shenzhen, Tsinghua University, Shenzhen, China

    Zhenhua Guo

  10. Shenzhen University, Shenzhen, China

    Shiqi Yu

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Liao, R., Cao, C., Garcia, E.B., Yu, S., Huang, Y. (2017). Pose-Based Temporal-Spatial Network (PTSN) for Gait Recognition with Carrying and Clothing Variations. In: Zhou, J., et al. Biometric Recognition. CCBR 2017. Lecture Notes in Computer Science(), vol 10568. Springer, Cham. https://doi.org/10.1007/978-3-319-69923-3_51

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  • DOI: https://doi.org/10.1007/978-3-319-69923-3_51

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69922-6

  • Online ISBN: 978-3-319-69923-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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