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

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

1 Citation (Scopus)

Abstract

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).

Original languageEnglish
Title of host publicationProceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019
EditorsKokou Yetongnon, Albert Dipanda, Gabriella Sanniti di Baja, Luigi Gallo, Richard Chbeir
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages447-453
Number of pages7
ISBN (Electronic)9781728156866
DOIs
Publication statusPublished - 2019 Nov
Event15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019 - Sorrento, Italy
Duration: 2019 Nov 262019 Nov 29

Publication series

NameProceedings - 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
CountryItaly
CitySorrento
Period19/11/2619/11/29

Keywords

  • Shot Detection
  • Sports Video Analysis
  • Tennis

ASJC Scopus subject areas

  • Computer Science Applications
  • Signal Processing
  • Media Technology
  • Computer Networks and Communications

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