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학술대회 A Study on American Football Player Tracking based on Video through deep learning and GPS convergence
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저자
이정수, 문성원, 남도원, 이지원, 오아름, 유원영
발행일
202110
출처
International Conference on Information and Communication Technology Convergence (ICTC) 2021, pp.1114-1116
DOI
https://dx.doi.org/10.1109/ICTC52510.2021.9621106
협약과제
21HH5800, 영상 내 객체간 관계 분석 기반 해상 선박/구조물 상세 식별 콘텐츠 기술 개발, 남도원
초록
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.
키워드
deep learning, detection and tracking, GPS, Tracking the players
KSP 제안 키워드
American football, Detection and tracking, Experiment results, Failure Rate, Object location, Player Tracking, Tracking failure, Tracking object, deep learning(DL), global positioning system(GPS), object Tracking