Spatio-Temporal Analysis of Team Sports.

ACM Comput. Surv.(2017)

引用 254|浏览23
暂无评分
摘要
Team-based invasion sports such as football, basketball, and hockey are similar in the sense that the players are able to move freely around the playing area and that player and team performance cannot be fully analysed without considering the movements and interactions of all players as a group. State-of-the-art object tracking systems now produce spatio-temporal traces of player trajectories with high definition and high frequency, and this, in turn, has facilitated a variety of research efforts, across many disciplines, to extract insight from the trajectories. We survey recent research efforts that use spatio-temporal data from team sports as input and involve non-trivial computation. This article categorises the research efforts in a coherent framework and identifies a number of open research questions.
更多
查看译文
关键词
Trajectory,spatio-temporal data,sports analysis,spatial subdivision,network analysis,data mining,machine learning,performance metrics,basketball,soccer,football,american football,handball,hockey
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要