ViSTec: Video Modeling for Sports Technique Recognition and Tactical Analysis

arXiv:2402.15952v1 Announce Type: new
Abstract: The immense popularity of racket sports has fueled substantial demand in tactical analysis with broadcast videos. However, existing manual methods require laborious annotation, and recent attempts leveraging video perception models are limited to low-level annotations like ball trajectories, overlooking tactics that necessitate an understanding of stroke techniques. State-of-the-art action segmentation models also struggle with technique recognition due to frequent occlusions and motion-induced blurring in racket sports videos. To address these challenges, We propose ViSTec, a …

analysis arxiv cs.cv modeling recognition sports type video