Challenges and Opportunities for Computer Vision in Real-life Soccer Analytics
It addresses the problem of extracting performance metrics from sports data for players and teams, but appears incremental as it focuses on discussing existing challenges rather than presenting new solutions.
The paper explores the challenges and opportunities of applying computer vision to soccer analytics, using a multi-camera setup as a framework to discuss real-life issues for machine learning algorithms.
In this paper, we explore some of the applications of computer vision to sports analytics. Sport analytics deals with understanding and discovering patterns from a corpus of sports data. Analysing such data provides important performance metrics for the players, for instance in soccer matches, that could be useful for estimating their fitness and strengths. Team level statistics can also be estimated from such analysis. This paper mainly focuses on some the challenges and opportunities presented by sport video analysis in computer vision. Specifically, we use our multi-camera setup as a framework to discuss some of the real-life challenges for machine learning algorithms.