Player pose analysis in tennis video based on pose estimation

Ryunosuke Kurose, Masaki Hayashi, Takeo Ishii, Yoshimitsu Aoki

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    The demand for sports video analysis is expanding. Sports video analysis is used to analyze their own play and play of opponent players, and visualize movement and ability of players. Scientific and objective analysis become possible by incorporating video analysis. It is desired to improve the competition level by feeding back the analysis results to the players. Therefore, in this research, in the case of feeding back the analysis result to the athlete, research purpose is to realize a method which can understand and evaluate the details of the form hitting the ball in detail. First, joint position coordinates are estimated from input RGB tennis images by a posture estimation method. The joint position coordinates in each frame at the time of shot are classified using unsupervised method and represented by BoW. The feature vector is designed by combining this with the shot position. The probability of shot success is predicted using this feature vector. By visualizing BoW of the shot with the high probability of success and the high failure probability, it is possible to extract and compare poses that are likely to appear in each case without giving correct labels.

    Original languageEnglish
    Title of host publication2018 International Workshop on Advanced Image Technology, IWAIT 2018
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages1-4
    Number of pages4
    ISBN (Electronic)9781538626153
    DOIs
    Publication statusPublished - 2018 May 30
    Event2018 International Workshop on Advanced Image Technology, IWAIT 2018 - Chiang Mai, Thailand
    Duration: 2018 Jan 72018 Jan 9

    Other

    Other2018 International Workshop on Advanced Image Technology, IWAIT 2018
    CountryThailand
    CityChiang Mai
    Period18/1/718/1/9

    Keywords

    • feedback
    • joint coordinates
    • pose estimation
    • tennis
    • unsupervised method
    • video analysis
    • visualization

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Computer Vision and Pattern Recognition
    • Media Technology

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