SportsTrack: An Innovative Method for Tracking Athletes in Sports Scenes

• URL: http://arxiv.org/abs/2211.07173v1
• Date: Mon, 14 Nov 2022 08:09:38 GMT
• Title: SportsTrack: An Innovative Method for Tracking Athletes in Sports Scenes
• Authors: Jie Wang, Yuzhou Peng, Xiaodong Yang, Ting Wang, Yanming Zhang
• Abstract summary: SportsMOT competition aims to solve multiple object tracking of athletes in different sports scenes such as basketball or soccer. Previous MOT methods can not match enough high-quality tracks of athletes. We introduce an innovative tracker named SportsTrack, we utilize tracking by detection as our detection paradigm. We reached the top 1 tracking score (76.264 HOTA) in the ECCV 2022 DeepAction SportsMOT competition.
• Score: 14.901600628787351
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The SportsMOT competition aims to solve multiple object tracking of athletes in different sports scenes such as basketball or soccer. The competition is challenging because of the unstable camera view, athletes' complex trajectory, and complicated background. Previous MOT methods can not match enough high-quality tracks of athletes. To pursue higher performance of MOT in sports scenes, we introduce an innovative tracker named SportsTrack, we utilize tracking by detection as our detection paradigm. Then we will introduce a three-stage matching process to solve the motion blur and body overlapping in sports scenes. Meanwhile, we present another innovation point: one-to-many correspondence between detection bboxes and crowded tracks to handle the overlap of athletes' bodies during sports competitions. Compared to other trackers such as BOT-SORT and ByteTrack, We carefully restored edge-lost tracks that were ignored by other trackers. Finally, we reached the top 1 tracking score (76.264 HOTA) in the ECCV 2022 DeepAction SportsMOT competition.

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