Action Recognition in Sports Video Considering Location Information

Rina Ichige, Yoshimitsu Aoki

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

2 Citations (Scopus)


The purpose of this study is to develop a tactics analysis system using image recognition for rugby. With the Rugby World Cup in 2019 and the Tokyo Olympics in 2020, demand for sports video analysis is increasing. Rugby has more complicated play such as dense play than other sports, and the ball is hidden between players, making it difficult to track. By developing a high-precision analysis technology for rugby with few research cases, we thought that it could be used for other sports and industrial fields other than sports. In this research, we propose a method that adds spatial information to time-series information as a new feature. Using the coordinates obtained by projectively transforming the match video onto the bird’s-eye view image, play classification was performed using the player position, the ball position, and the dense area position as feature amounts. Also, in order to further improve the detection accuracy of the boundaries between plays, attention was paid to the positional relationship of each player on the field.

Original languageEnglish
Title of host publicationFrontiers of Computer Vision - 26th International Workshop, IW-FCV 2020, Revised Selected Papers
EditorsWataru Ohyama, Soon Ki Jung
Number of pages15
ISBN (Print)9789811548178
Publication statusPublished - 2020
EventInternational Workshop on Frontiers of Computer Vision, IW-FCV 2020 - Ibusuki, Japan
Duration: 2020 Feb 202020 Feb 22

Publication series

NameCommunications in Computer and Information Science
Volume1212 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937


ConferenceInternational Workshop on Frontiers of Computer Vision, IW-FCV 2020


  • Dense play
  • Heatmap features
  • Subdivision of play area

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics


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