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Automatic quality evaluation of parade by variance of postures of a platoon on single video camera logs

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Abstract

The highly synchronized parade can impress audiences how strong the troops seem to be, whereas it is difficult to train for the good parade because of its complex collective behavior. However, there is no scientific research about the important factor to train and produce a good parade is. One of the bottlenecks to the scientific approach is the difficulty of measurement of the quality of a group as same as other swarm researches. In this paper, we measured the posture data of members in the parade with OpenPose, which is a cutting-edge pose estimation technology of deep learning. By this measurement, we propose a numerical evaluation for the quality of the parade, and it is confirmed by the questionnaire. In conclusion, our evaluation method is applicable for the quantitative evaluation, and it was suggested that the variation level of the arm swing angles was related to the quality of the parade. This paper is based on the paper presented at the proceedings of the 3rd International Symposium on Swarm Behavior and Bio-Inspired Robotics [1].

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Notes

  1. Personal conversation with Omi J. about Group Action of Nippon Sport Science University,19th Aug., 2020.

References

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Authors and Affiliations

  1. National Defense Academy of Japan, Hashirimizu 1-10-20, Yokosuka, Kanagawa, Japan

    Masao Kubo, Yohei Okugawa & Hiroshi Sato

Authors
  1. Masao Kubo
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  2. Yohei Okugawa
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  3. Hiroshi Sato
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Corresponding author

Correspondence to Masao Kubo.

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This work was presented in part at the 3rd International Symposium on Swarm Behavior and Bio-Inspired Robotics (Okinawa, Japan, November 20–22, 2019).

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Kubo, M., Okugawa, Y. & Sato, H. Automatic quality evaluation of parade by variance of postures of a platoon on single video camera logs. Artif Life Robotics 25, 537–543 (2020). https://doi.org/10.1007/s10015-020-00644-0

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  • DOI: https://doi.org/10.1007/s10015-020-00644-0

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