Pattern Recognition for Tennis Tactics using Hidden Markov Model from Rally Series

DOI
  • MIYAHARA Natsuki
    Graduate School of Library Information and Media Studies, University of Tsukuba
  • TEZUKA Taro
    Faculty of Library Information and Media Science, University of Tsukuba
  • NAKAUCHI Yasushi
    Faculty of Engineering, Information and Systems, University of Tsukuba

Bibliographic Information

Other Title
  • 隠れマルコフモデルを用いたテニスにおけるラリー系列からのパターン発見

Abstract

<p>In this paper, we propose pattern recognition for tennis tactics using ball trajectory data from motion capture system. The purpose of the study is to adapt machine learning in order to implement feature extraction of rallies in tennis game using positions of ball bounce. We modeled this task as time-series data statistical modeling based on the Hidden Markov Model. We also conducted experiments and we verified the dispersion of the mixture component and the centroid, corresponding to four types of tennis court area division. Moreover, we implemented feature extraction of rally according to the initial state probability and the state transition probability.</p>

Journal

Details 詳細情報について

  • CRID
    1390845712979103616
  • NII Article ID
    130007423634
  • DOI
    10.11517/pjsai.jsai2018.0_2h201
  • Text Lang
    ja
  • Data Source
    • JaLC
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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