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FollowMeUp Sports: New Benchmark for 2D Human Keypoint Recognition

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Pattern Recognition and Computer Vision (PRCV 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11859))

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Abstract

Human pose estimation has made significant advancement in recent years. However, the existing datasets are limited in their coverage of pose variety. In this paper, we introduce a novel benchmark “FollowMeUp Sports” that makes an important advance in terms of specific postures, self-occlusion and class balance, a contribution that we feel is required for future development in human body models. This comprehensive dataset was collected using an established taxonomy of over 200 standard workout activities with three different shot angles. The collected videos cover a wider variety of specific workout activities than previous datasets including push-up, squat and body moving near the ground with severe self-occlusion or occluded by some sport equipment and outfits. Given these rich images, we perform a detailed analysis of the leading human pose estimation approaches gaining insights for the success and failures of these methods.

Y. Huang, B. Sun, H. Kan and J. Zhuang—Equal contribution.

Y. Huang—The work was done at Keep Inc. The research was partially supported by the National Key Research and Development Program of China (2017YFB1002803).

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Author information

Authors and Affiliations

  1. Alibaba Business School, Hangzhou Normal University, Hangzhou, China

    Ying Huang

  2. Keep Inc., Beijing, China

    Bin Sun & Haipeng Kan

  3. Intelligent Computing and Machine Learning Lab, School of ASEE, Beihang University, Beijing, China

    Jiankai Zhuang & Zengchang Qin

Authors
  1. Ying Huang
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  2. Bin Sun
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  3. Haipeng Kan
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  4. Jiankai Zhuang
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  5. Zengchang Qin
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Corresponding author

Correspondence to Ying Huang .

Editor information

Editors and Affiliations

  1. School of EECS, Peking University, Beijing, China

    Zhouchen Lin

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

    Liang Wang

  3. Nanjing University of Science and Technology, Nanjing, China

    Jian Yang

  4. Xidian University, Xi’an, China

    Guangming Shi

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

    Tieniu Tan

  6. Institute of Artificial Intelligence, Xi’an Jiaotong University, Xi’an, China

    Nanning Zheng

  7. Chinese Academy of Sciences, Beijing, China

    Xilin Chen

  8. Northwestern Polytechnical University, Xi’an, China

    Yanning Zhang

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Huang, Y., Sun, B., Kan, H., Zhuang, J., Qin, Z. (2019). FollowMeUp Sports: New Benchmark for 2D Human Keypoint Recognition. In: Lin, Z., et al. Pattern Recognition and Computer Vision. PRCV 2019. Lecture Notes in Computer Science(), vol 11859. Springer, Cham. https://doi.org/10.1007/978-3-030-31726-3_10

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  • DOI: https://doi.org/10.1007/978-3-030-31726-3_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-31725-6

  • Online ISBN: 978-3-030-31726-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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