References
- Arbués-Sangüesa, A., Ballester, C., & Haro, G. (2019). Single-camera basketball tracker through pose and semantic feature fusion. International Journal of Information, Control and Computer Sciences, 12(7).
https://doi.org/10.5281/zenodo.3346759 - Baumgartner, T., & Klatt, S. (2023). Monocular 3D human pose estimation for sports broadcasts using partial sports field registration. arXiv.
https://doi.org/10.48550/arXiv.2304.04437 - Bewley, A., Ge, Z., Ott, L., Ramos, F., & Upcroft, B. (2016). Simple online and realtime tracking. arXiv.
https://doi.org/10.48550/arXiv.1602.00763 - Bishop, C. M. (2006). Pattern recognition and machine learning. Springer.
- Debidatta, D., Aytar, Y., Tompson, J., Sermanet, P., & Zisserman, A. (2019). Temporal cycle-consistency learning. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 1801–1810). IEEE.
https://doi.org/10.48550/arXiv.1904.07846 - Doucet, A., de Freitas, N., & Gordon, N. (Eds.). (2001). Sequential Monte Carlo methods in practice. Springer.
- Hartley, R., & Zisserman, A. (2004). Multiple view geometry in computer vision (2nd ed.). Cambridge University Press.
- Hu, Q., Scott, A., Yeung, C., Xie, Y., Lin, T., & Zhao, W. (2024). Basketball-SORT: An association method for complex multi-object occlusion problems in basketball multi-object tracking. Multimedia Tools and Applications, 83, 86281–86297.
https://doi.org/10.1007/s11042-024-20360-2 - Idaka, Y., Yasuda, K., Ho, Y., & Tagawa, N. (2015). Analysis of basketball games using multiview images captured by handheld video. ITE Technical Report, 39(49), 13–16.
- Jin, L., Kulkarni, N., & Fouhey, D. (2024). 3DFIRES: Few image 3D reconstruction for scenes with hidden surfaces. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 2802–2811). IEEE.
https://doi.org/10.48550/arXiv.2403.08768 - Karungaru, S., Tanioka, H., Matsuura, K., & Terada, K. (2023). Basketball players’ identification and tracking using a single fixed camera. In Proceedings of the 2023 17th International Conference on Signal-Image Technology and Internet-Based Systems (SITIS) (pp. 341–346). IEEE.
https://doi.org/10.1109/SITIS61268.2023.00062 - Kim, H., Choi, H. J., Kim, C., Yoon, J., & Ko, S. K. (2023). Ball trajectory inference from multi-agent sports contexts using set transformer and hierarchical bi-LSTM. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 1458–1468). ACM.
https://doi.org/10.1145/3580305.3599481 - Pandya, N. A., & Chauhan, N. (2023). Survey paper on multi-view object detection: Challenges and techniques. In M. Tuba, S. Akashe, & A. Joshi (Eds.), ICT infrastructure and computing (Vol. 520, pp. 1–20). Springer.
https://doi.org/10.1007/978-981-19-5331-6_1 - Petilla, C. A. B., Yap, G. D. G., Zheng, N. Y., Yuson, P. L. L., & Ilao, J. P. (2018). Single player tracking in multiple sports videos. In J. Billingsley & P. Brett (Eds.), Mechatronics and machine vision in practice 3 (pp. 73–83). Springer.
https://doi.org/10.1007/978-3-319-76947-9_6 - Si, C., Jing, Y., Wang, W., Wang, L., & Tan, T. (2018). Skeleton-based action recognition with spatial reasoning and temporal stack learning. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 1034–1042). IEEE.
https://doi.org/10.48550/arXiv.1805.02335 - Singhal, A. (2001). Modern information retrieval: A brief overview. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering, 24(4), 35–43.
- Sports-Log. (2024). Top 10 world rankings for the number of athletes participating in sports in 2024! Popular sports in Japan explained!
https://sports-log.com/sports-competition-population-world-ranking/ - Szymanowicz, S., Rupprecht, C., & Vedaldi, A. (2024). Splatter image: Ultra-fast single-view 3D reconstruction. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 4551–4560). IEEE.
https://openaccess.thecvf.com - Tan, M., & Le, Q. V. (2019). EfficientNet: Rethinking model scaling for convolutional neural networks. In Proceedings of the International Conference on Machine Learning (ICML) (pp. 6105–6114). PMLR.
https://arxiv.org/abs/1905.11946 - Tsuji, R., Terada, K., & Karungaru, S. (2019). UAV video analysis of basketball. IEEJ Technical Meeting Papers, PI-19-075, 15–20.
- Vorobev, D., Prosvetov, A., & Daou, K. (2025). Real-time localization of a soccer ball from a single camera. arXiv.
https://doi.org/10.48550/arXiv.2506.07981 - Yahoo Finance. (2025, April 10). WNBA to use optical tracking to enhance player analysis.
https://finance.yahoo.com/news/wnba-optical-tracking-enhance-player-201640193.html - Yoon, Y., Hwang, H., Choi, Y., Joo, M., Oh, H., & Park, I. (2019). Analyzing basketball movements and pass relationships using real-time object tracking techniques based on deep learning. IEEE Access, 7, 56564–56576.
https://doi.org/10.1109/ACCESS.2019.2913953