Suggestion of Strategy Framework for Ice-Hockey Using Videos

DOI

Bibliographic Information

Other Title
  • アイスホッケー動画を用いた戦略分析フレームワークの提案

Abstract

<p>In recent years, the NHL, the world's largest ice hockey league, is actively conducting strategic analysis using game videos. However, most services use high-performance and expensive cameras and sensors, and therefore it is difficult for amateur teams to conduct that kind of analysis. This paper proposes a new framework that analyzes strategies automatically from only video shooting. We focus on the following topics: (1) Object detection (e.g., player, goal and face-off) using Mask-RCNN. (2) Homography transformation for estimation of players’ coordinates on hockey rink from positional relationship of objects. (3) Estimation of the expected goal values from players' coordinates and actions using a probabilistic classifier. We verified the accuracy of those using videos from NHL 2019-20. As a result, although some issues (e.g., false-positive, expected goal value accuracy) have to be resolved, we demonstrated that our method was sufficiently possible.</p>

Journal

Keywords

Details 詳細情報について

  • CRID
    1390003825189689216
  • NII Article ID
    130007857391
  • DOI
    10.11517/pjsai.jsai2020.0_4rin133
  • Text Lang
    ja
  • Data Source
    • JaLC
    • CiNii Articles
  • Abstract License Flag
    Disallowed

Report a problem

Back to top