A survey on soccer player detection and tracking with videos
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| Veröffentlicht in: | The Visual Computer vol. 41, no. 2 (Jan 2025), p. 815 |
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| Veröffentlicht: |
Springer Nature B.V.
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| Schlagworte: | |
| Online-Zugang: | Citation/Abstract Full Text Full Text - PDF |
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| Abstract: | Soccer is a popular sport, and there is a growing need for automated analysis of soccer videos, while the detection and tracking of the players is the indispensable prerequisite. In this paper, we first introduce and classify multi-object tracking and then present two mostly used multi-object tracking methods, DeepSort and TrackFormer. When multi-object tracking is applied to soccer scenarios, some preprocessing and post-processing are generally performed, with preprocessing including processing of the video, such as splicing and background removing, and post-processing including further applications, such as player mapping for a 2D stadium. By directly employing the two methods above, we test the real scene and train TrackFormer to get further results. Meanwhile, in order to facilitate researchers who are interested in multi-object tracking as well as in the direction of player tracking, recent advances in preprocessing and processing methods for soccer player tracking are given and future research directions are suggested. |
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| ISSN: | 0178-2789 1432-2315 |
| DOI: | 10.1007/s00371-024-03367-6 |
| Quelle: | Advanced Technologies & Aerospace Database |