Pattern Recognition for Tennis Tactics using Hidden Markov Model from Rally Series
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- MIYAHARA Natsuki
- Graduate School of Library Information and Media Studies, University of Tsukuba
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- TEZUKA Taro
- Faculty of Library Information and Media Science, University of Tsukuba
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- NAKAUCHI Yasushi
- Faculty of Engineering, Information and Systems, University of Tsukuba
Bibliographic Information
- Other Title
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- 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
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- Proceedings of the Annual Conference of JSAI
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Proceedings of the Annual Conference of JSAI JSAI2018 (0), 2H201-2H201, 2018
The Japanese Society for Artificial Intelligence
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Details 詳細情報について
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- CRID
- 1390845712979103616
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- NII Article ID
- 130007423634
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- Text Lang
- ja
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- Data Source
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- JaLC
- CiNii Articles
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- Abstract License Flag
- Disallowed