Shot detection in racket sport video at the frame level using a recurrent neural network

Shuto Horie, Yuji Sato, Junko Furuyama, Masamoto Tanabiki, Yoshimitsu Aoki

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

In recent years, there has been a demand in the sports industry to reduce the burden of data collection and video editing for tactical analysis. To achieve these, a system that can recognize the game context is needed. In this study, we proposed a method to identify the player's shot timing at the frame level during a ball-striking sport. In this study, players' shots were detected in video of a tennis match. It was shown that shots could be detected with an F-score value of 87% or more within an error range of 1 frame (0.033 sec) by considering time-series information using a recurrent neural network. This technology is expected to be applied not only to tennis, but also to other sports that involve ball shots, such as table tennis, baseball, and volleyball. At the same time, it can be used to detect moments of a specific action (for example, touching or hitting an object).

本文言語English
ホスト出版物のタイトルProceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019
編集者Kokou Yetongnon, Albert Dipanda, Gabriella Sanniti di Baja, Luigi Gallo, Richard Chbeir
出版社Institute of Electrical and Electronics Engineers Inc.
ページ447-453
ページ数7
ISBN(電子版)9781728156866
DOI
出版ステータスPublished - 2019 11月
イベント15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019 - Sorrento, Italy
継続期間: 2019 11月 262019 11月 29

出版物シリーズ

名前Proceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019

Conference

Conference15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019
国/地域Italy
CitySorrento
Period19/11/2619/11/29

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • 信号処理
  • メディア記述
  • コンピュータ ネットワークおよび通信

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