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Least-Squares Estimation of Keypoint Coordinate for Human Pose Estimation

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Pattern Recognition and Computer Vision (PRCV 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13536))

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Abstract

The research on human pose estimation has recently been promoted to a new high degree. As a result, existing methods that are widely used but flawed in theory must be rethought. Most researchers focus on enhancing network structure and data processing details, yet neglect to study encoding-decoding methods for keypoint coordinate. In this paper, we rethink recent encoding-decoding methods and further propose a new, elegant and reliable one. Our method is referred to as Least-squares Estimation of Keypoint Coordinate (LSEC), which is a plug-in and can be conveniently used in recent state-of-the-art (SOTA) human pose estimation models. LSEC is mathematically rigorous and unbiased, and it can compensate for the inherent bias introduced by the existing encoding-decoding methods. Besides, LSEC greatly improves the robustness of Gaussian heatmap based human pose estimation methods against adversarial attack by noise. Experiments demonstrate the effective performance and robustness of our proposed method. We will release the source code later.

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Author information

Authors and Affiliations

  1. University of Science and Technology of China, Hefei, China

    Linhua **ang & Zengfu Wang

  2. Institute of Intelligent Machines, Chinese Academy of Sciences, Bei**g, China

    Zengfu Wang

  3. National Engineering Research Center of Speech and Language Information Processing, Hefei, China

    Linhua **ang, Jia Li & Zengfu Wang

  4. Hefei University of Technology, Hefei, China

    Jia Li

Authors
  1. Linhua **ang
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  2. Jia Li
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  3. Zengfu Wang
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Corresponding author

Correspondence to Zengfu Wang .

Editor information

Editors and Affiliations

  1. Southern University of Science and Technology, Shenzhen, China

    Shiqi Yu

  2. Institute of Automation, Chinese Academy of Sciences, Bei**g, China

    Zhaoxiang Zhang

  3. Hong Kong Baptist University, Hong Kong, China

    Pong C. Yuen

  4. Northwestern Polytechnical University, **'an, China

    Junwei Han

  5. Institute of Automation, Chinese Academy of Sciences, Bei**g, China

    Tieniu Tan

  6. Hong Kong Baptist University, Hong Kong, China

    Yike Guo

  7. Sun Yat-sen University, Guangzhou, China

    Jianhuang Lai

  8. Southern University of Science and Technology, Shenzhen, China

    Jianguo Zhang

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**ang, L., Li, J., Wang, Z. (2022). Least-Squares Estimation of Keypoint Coordinate for Human Pose Estimation. In: Yu, S., et al. Pattern Recognition and Computer Vision. PRCV 2022. Lecture Notes in Computer Science, vol 13536. Springer, Cham. https://doi.org/10.1007/978-3-031-18913-5_35

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  • DOI: https://doi.org/10.1007/978-3-031-18913-5_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-18912-8

  • Online ISBN: 978-3-031-18913-5

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