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Conference Paper
A Study on American Football Player Tracking based on Video through deep learning and GPS convergence
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- Authors
- JungSoo Lee, Sungwon Moon, Do-Won Nam, Jiwon Lee, Ah Reum Oh, Wonyoung Yoo
- Issue Date
- 2021-10
- Citation
- International Conference on Information and Communication Technology Convergence (ICTC) 2021, pp.1114-1116
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- When tracking objects (players, referees, etc.) in a game using deep learning, tracking often fails due to occlusion between objects. In this paper, we track the location of objects in the stadium through video tracking using deep learning. and we fused the GPS(Global Positioning System), which has a large error but can maintain the ID of the object even when the objects overlap so that the tracking can be done correctly even in the overlapping phenomenon between objects. From the experiment results, we could confirm that the object tracking failure rate can be reduced and the accuracy of the object location can be increased through the convergence of deep learning and GPS.
- KSP Keywords
- American football, Experiment results, Global positioning system(GPS), Object Tracking, Player Tracking, Tracking failure, Tracking objects, deep learning(DL), failure rate, object location, video tracking