ScoreActuary: Hoop-Centric Trajectory-Aware Network for Fine-Grained Basketball Shot Analysis

Ting-Yang Kao, Tse-Yu Pan, Chen-Ni Chen, Tsung-Hsun Tsai, Hung-Kuo Chu, Min-Chun Hu

Abstract: We propose a fine-grained basketball shot analysis system called ScoreActuary to analyze the players' shot events, which can be applied to game analysis, player training, and highlight generation. Given a basketball video as input, our system first detects/segments shot candidates and then analyzes "Shot Type", "Shot Result", and "Ball Status" of each shot candidate in real-time. Our approach is composed of a customized object detector and a trajectory-aware network to learn the information of ball trajectory. Compared to the existing methods that analyze basketball shots, our algorithm can better handle videos with arbitrary camera movements while improving the accuracy. To the best of our knowledge, this work is the first system that can analyze fine-grained shot events accurately in real basketball games with arbitrary camera movements.