EIoU-distance loss: an automated team-wise player detection and tracking with jersey colour recognition in soccer
The surge in demand for advanced operations in sports video analysis has underscored the crucial role of multiple object tracking. This study addresses the escalating need for efficient and accurate player and referee identification in sports video analysis. The challenge of identity switching among...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | Connection Science |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/09540091.2023.2291991 |
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| author | Banoth Thulasya Naik Mohammad Farukh Hashmi Aditya Gupta |
| author_facet | Banoth Thulasya Naik Mohammad Farukh Hashmi Aditya Gupta |
| author_sort | Banoth Thulasya Naik |
| collection | DOAJ |
| description | The surge in demand for advanced operations in sports video analysis has underscored the crucial role of multiple object tracking. This study addresses the escalating need for efficient and accurate player and referee identification in sports video analysis. The challenge of identity switching among players, especially those with similar appearances, complicates multi-player tracking. Existing algorithms relying on manually labeled data face limitations, particularly with changes in jersey colors. This paper introduces an automated algorithm employing Intersection over Union (IoU) loss and Euclidean Distance (EUD), termed EIoU-Distance Loss, to track players and referees. The method prioritizes identity coherence, aiming to mitigate challenges associated with player and referee recognition. Comprising BackgroundSubtractionMOG2 for player and referee detection and IoU with EUD for connecting nodes across frames, the proposed approach enhances tracking performance, ensuring a clear distinction between different identities. This innovative method addresses critical issues in sports video analysis, offering a robust solution for tracking players and referees in dynamic game scenarios. |
| format | Article |
| id | doaj-art-472fa2138486443c8a7d192d23a58530 |
| institution | OA Journals |
| issn | 0954-0091 1360-0494 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Connection Science |
| spelling | doaj-art-472fa2138486443c8a7d192d23a585302025-08-20T02:17:52ZengTaylor & Francis GroupConnection Science0954-00911360-04942024-12-0136110.1080/09540091.2023.2291991EIoU-distance loss: an automated team-wise player detection and tracking with jersey colour recognition in soccerBanoth Thulasya Naik0Mohammad Farukh Hashmi1Aditya Gupta2Department of Electronics and Communication Engineering, National Institute of Technology, Warangal, IndiaDepartment of Electronics and Communication Engineering, National Institute of Technology, Warangal, IndiaDepartment of Information and Communication Technology, University of Agder, Grimstad, NorwayThe surge in demand for advanced operations in sports video analysis has underscored the crucial role of multiple object tracking. This study addresses the escalating need for efficient and accurate player and referee identification in sports video analysis. The challenge of identity switching among players, especially those with similar appearances, complicates multi-player tracking. Existing algorithms relying on manually labeled data face limitations, particularly with changes in jersey colors. This paper introduces an automated algorithm employing Intersection over Union (IoU) loss and Euclidean Distance (EUD), termed EIoU-Distance Loss, to track players and referees. The method prioritizes identity coherence, aiming to mitigate challenges associated with player and referee recognition. Comprising BackgroundSubtractionMOG2 for player and referee detection and IoU with EUD for connecting nodes across frames, the proposed approach enhances tracking performance, ensuring a clear distinction between different identities. This innovative method addresses critical issues in sports video analysis, offering a robust solution for tracking players and referees in dynamic game scenarios.https://www.tandfonline.com/doi/10.1080/09540091.2023.2291991Soccer playerjersey colourdetectiontrackingcomputer vision |
| spellingShingle | Banoth Thulasya Naik Mohammad Farukh Hashmi Aditya Gupta EIoU-distance loss: an automated team-wise player detection and tracking with jersey colour recognition in soccer Connection Science Soccer player jersey colour detection tracking computer vision |
| title | EIoU-distance loss: an automated team-wise player detection and tracking with jersey colour recognition in soccer |
| title_full | EIoU-distance loss: an automated team-wise player detection and tracking with jersey colour recognition in soccer |
| title_fullStr | EIoU-distance loss: an automated team-wise player detection and tracking with jersey colour recognition in soccer |
| title_full_unstemmed | EIoU-distance loss: an automated team-wise player detection and tracking with jersey colour recognition in soccer |
| title_short | EIoU-distance loss: an automated team-wise player detection and tracking with jersey colour recognition in soccer |
| title_sort | eiou distance loss an automated team wise player detection and tracking with jersey colour recognition in soccer |
| topic | Soccer player jersey colour detection tracking computer vision |
| url | https://www.tandfonline.com/doi/10.1080/09540091.2023.2291991 |
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