no code implementations • 22 May 2022 • Kanav Vats, Mehrnaz Fani, David A. Clausi, John S. Zelek
Tracking and identifying players is an important problem in computer vision based ice hockey analytics.
no code implementations • 6 Oct 2021 • Kanav Vats, Pascale Walters, Mehrnaz Fani, David A. Clausi, John Zelek
The player identification model further takes advantage of the available NHL game roster data to obtain a player identification accuracy of 83%.
no code implementations • 17 Aug 2021 • Kanav Vats, Mehrnaz Fani, David A. Clausi, John Zelek
Identifying players in sports videos by recognizing their jersey numbers is a challenging task in computer vision.
no code implementations • 21 May 2021 • Kanav Vats, Mehrnaz Fani, David A. Clausi, John Zelek
In this paper, we introduce and implement a network for puck localization in broadcast hockey video.
no code implementations • 22 Apr 2021 • Mehrnaz Fani, Pascale Berunelle Walters, David A. Clausi, John Zelek, Alexander Wong
To localize the frames on the ice-rink model, a ResNet18-based regressor is implemented and trained, which regresses to four control points on the model in a frame-by-frame fashion.
no code implementations • 13 Apr 2020 • Kanav Vats, Mehrnaz Fani, Pascale Walters, David A. Clausi, John Zelek
Experimental results demonstrate the effectiveness of the network by obtaining a 55% average F1 score on the NHL dataset and by achieving competitive performance compared to the state of the art on the SoccerNet dataset.
Ranked #4 on Action Spotting on SoccerNet