An AI-Based Curling Game System for Winter Olympics

Abstract

The real-time application of artificial intelligence (AI) technologies in sports is a long-standing challenge owing to large spatial sports field, complexity, and uncertainty of real-world environment, etc. Although some AI-based systems have been applied to sporting events such as tennis, basketball, and football, they are replayed after the game rather than applied in real time. Here, we present an AI-based curling game system, termed CurlingHunter, which can display actual trajectories, predicted trajectories, and house regions of curling during the games via a giant screen in curling stadiums and a live streaming media platform on the internet in real time, so as to assist the game, improve the interest of watching game, help athletes train, etc. We provide a complete description of CurlingHunter’ architecture and a thorough evaluation of its performances and demonstrate that CurlingHunter possesses remarkable real-time performance (~9.005 ms), high accuracy ( cm under measurement