| Title |
Multiple object tracking for video-based sports analysis / |
| Authors |
Gudauskas, Julius ; Matusevičius, Žygimantas |
| Full Text |
|
| Is Part of |
CEUR workshop proceedings: IVUS 2021: Information society and university studies 2021: Proceedings of the 26th international conference on information society and university studies (IVUS 2021), Kaunas, Lithuania, April 23, 2021 / edited by: I. Veitaitė, A. Lopata, T. Krilavičius, M. Woźniak.. Aachen : CEUR-WS. 2021, vol. 2915, art. no. 1, p. 1-10.. ISSN 1613-0073 |
| Keywords [eng] |
multiple object tracking ; MOT ; SOT ; CNN, ONNX ; goalball ; boosting ; CSR-DCF ; KCF ; MOSSE ; TLD |
| Abstract [eng] |
Multiple object tracking (MOT) is a challenging task in computer vision. Many algorithms have been proposed to track multiple targets for video surveillance, team-sport analysis, or human–computer interaction. Recent studies have already indicated that multiple object tracking could provide valuable information in team sports analysis. Therefore, in this paper, we investigate object tracking techniques for paralympic team sport – goalball. Different tracking methods have been implemented and compared, evaluating prediction accuracy and performance speed in players and the ball tracking. |
| Published |
Aachen : CEUR-WS |
| Type |
Conference paper |
| Language |
English |
| Publication date |
2021 |
| CC license |
|
