Journal of the Japan society of photogrammetry and remote sensing
Online ISSN : 1883-9061
Print ISSN : 0285-5844
ISSN-L : 0285-5844
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Volume 61, Issue 4
Displaying 1-14 of 14 articles from this issue
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Preface
Original Papers
  • Research on Matching Players Before and After Occlusion for Field Sports
    Wenyuan JIANG, Yuhei YAMAMOTO, Kenji NAKAMURA, Chihiro TANAKA, Shigeno ...
    2022 Volume 61 Issue 4 Pages 218-240
    Published: 2022
    Released on J-STAGE: September 01, 2023
    DOIhttps://doi.org/10.4287/jsprs.61.218
    JOURNAL FREE ACCESS
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    In field sports, to realize tactical analysis, many techniques for athlete detection, identification and tracking by analyzing videos have been developed. However, many techniques have the same problems that the accuracy of detection, identification and tracking will decline in quality while athletes are occluding. In this research, the authors focus on the fact that the features of each athlete before and after occlusion are approximated, and then developed the method for identifying athletes with their features before and after occlusion. In the results, we were able to solve the problem of degrading detection, identification and tracking accuracy in the occlusion interval.

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  • Research on Removing Shadow of Field Sport Players Using GAN
    Wenyuan JIANG, Yuhei YAMAMOTO, Kenji NAKAMURA, Chihiro TANAKA, Kazuma ...
    2022 Volume 61 Issue 4 Pages 241-255
    Published: 2022
    Released on J-STAGE: September 01, 2023
    DOIhttps://doi.org/10.4287/jsprs.61.241
    JOURNAL FREE ACCESS
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    In recent years, the utilization of ICT for field sports has been promoted in Japan. And then, a lot of researches have been conducted on tactical analysis using positions and trajectories of players obtained from play video data. However, in many of them, an area of an athlete may be misidentified as area containing shadow or area of only shadow, which leads to a problem of acquiring accurate positions of athletes. Therefore, in this research, a method to remove the shadows of players from soccer play videos by using pix2pix, a type of GAN, to generate shadow-free videos is proposed and implemented. As a result, it was verified through experiments that the shadows of athletes could be removed accurately. Furthermore, the effectiveness of the proposed method was also confirmed by tracking accuracy comparison of an existing person tracking method with and without shadow removal.

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