{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T00:22:48Z","timestamp":1758846168295,"version":"3.44.0"},"publisher-location":"Cham","reference-count":40,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032061669","type":"print"},{"value":"9783032061676","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T00:00:00Z","timestamp":1758844800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T00:00:00Z","timestamp":1758844800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-06167-6_2","type":"book-chapter","created":{"date-parts":[[2025,9,25]],"date-time":"2025-09-25T18:51:39Z","timestamp":1758826299000},"page":"18-35","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["YOCO-Sport: An End-to-End Framework for\u00a0Deep Learning-Based Camera Calibration from\u00a0Sports Broadcast Footage"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-1272-3191","authenticated-orcid":false,"given":"Gerhardt","family":"Breytenbach","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1868-0759","authenticated-orcid":false,"given":"Jacomine","family":"Grobler","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,9,26]]},"reference":[{"key":"2_CR1","unstructured":"Abdel-Aziz, Y.I., Karara, H.M.: Direct linear transformation from comparator coordinates into object space coordinates in close range photogrammetry. In: Proceedings of the Symposium on Close-Range Photogrammetry, Urbana (IL), USA, pp. 1\u201319 (1971)"},{"key":"2_CR2","doi-asserted-by":"publisher","unstructured":"Bebie, T., Bieri, H.: SoccerMan-reconstructing soccer games from video sequences. In: Proceedings of the 1998 International Conference on Image Processing (ICIP), vol. 1, pp. 898\u2013902. IEEE, Chicago (1998). https:\/\/doi.org\/10.1109\/ICIP.1998.723665","DOI":"10.1109\/ICIP.1998.723665"},{"key":"2_CR3","unstructured":"Breytenbach, G.: Badminton-Keys dataset. Roboflow Universe. https:\/\/universe.roboflow.com\/gerdos-computer-vision-games\/badminton-keys. Accessed 29 Apr 2025"},{"issue":"2","key":"2_CR4","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1007\/s42979-024-03636-0","volume":"6","author":"G Breytenbach","year":"2025","unstructured":"Breytenbach, G., Grobler, J.: Evaluating the accuracy of a generic field template for camera calibration in soccer broadcast footage. SN Comput. Sci. 6(2), 107 (2025). https:\/\/doi.org\/10.1007\/s42979-024-03636-0","journal-title":"SN Comput. Sci."},{"key":"2_CR5","doi-asserted-by":"publisher","unstructured":"Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. PAMI 8(6), 679\u2013698 (1986). https:\/\/doi.org\/10.1109\/TPAMI.1986.4767851","DOI":"10.1109\/TPAMI.1986.4767851"},{"key":"2_CR6","doi-asserted-by":"publisher","unstructured":"Chen, J., Little, J.J.: Sports camera calibration via synthetic data. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 2497\u20132504. IEEE\/CVF, Long Beach (2019). https:\/\/doi.org\/10.1109\/CVPRW.2019.00305","DOI":"10.1109\/CVPRW.2019.00305"},{"key":"2_CR7","doi-asserted-by":"publisher","unstructured":"Chu, Y.J., et al.: Sports field registration via keypoints-aware label condition. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 3523\u20133530. IEEE\/CVF, New Orleans (2022). https:\/\/doi.org\/10.1109\/CVPRW56347.2022.00396","DOI":"10.1109\/CVPRW56347.2022.00396"},{"key":"2_CR8","unstructured":"Dimensions.com: Badminton court dimensions. https:\/\/www.dimensions.com\/element\/badminton-court. Accessed 29 Apr 2025"},{"key":"2_CR9","doi-asserted-by":"publisher","unstructured":"Duda, R.O., Hart, P.E.: Use of the Hough transformation to detect lines and curves in pictures. Commun. ACM 15(1), 11\u201315 (1972). https:\/\/doi.org\/10.1145\/361237.361242","DOI":"10.1145\/361237.361242"},{"key":"2_CR10","unstructured":"Dwyer, B., Nelson, J., Hansen, T., et al.: Roboflow (Version 1.0) [Software]. https:\/\/roboflow.com. Accessed 29 Apr 2025"},{"key":"2_CR11","doi-asserted-by":"publisher","unstructured":"Dzia\u0142owski, K., Forczma\u0144ski, P.: Football players movement analysis in panning videos. In: Paszynski M., Kranzlm\u00fcller D., Krzhizhanovskaya V.V., Dongarra J.J., Sloot P.M.A. (eds.) Computational science \u2013 ICCS 2021, vol 12746, pp. 193\u2013206. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-77977-1_15","DOI":"10.1007\/978-3-030-77977-1_15"},{"issue":"6","key":"2_CR12","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1145\/358669.358692","volume":"24","author":"MA Fischler","year":"1981","unstructured":"Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381\u2013395 (1981). https:\/\/doi.org\/10.1145\/358669.358692","journal-title":"Commun. ACM"},{"key":"2_CR13","doi-asserted-by":"publisher","unstructured":"Ghassab, V., Maanicshah, K., Bouguila, N., Green, P.: REP-MODEL: a deep learning framework for replacing ad billboards in soccer videos. In: 2020 IEEE International Symposium on Multimedia, pp. 149\u2013153. IEEE (2020). https:\/\/doi.org\/10.1109\/ISM.2020.00032","DOI":"10.1109\/ISM.2020.00032"},{"key":"2_CR14","doi-asserted-by":"publisher","unstructured":"Giancola, S., Cioppa, A., Deli\u00e8ge, A., Magera, F., Somers, V., Kang, L.: SoccerNet 2022 challenges results. In: Proceedings of the 5th International ACM Workshop on Multimedia Content Analysis in Sports, pp. 75\u201386. ACM, New York (2022). https:\/\/doi.org\/10.1145\/3552437.3558545","DOI":"10.1145\/3552437.3558545"},{"key":"2_CR15","doi-asserted-by":"publisher","unstructured":"Guti\u00e9rrez-P\u00e9rez, M., Agudo, A.: PnLCalib: sports field registration via points and lines optimization. arXiv preprint arXiv:2404.08401 (2024). https:\/\/doi.org\/10.48550\/arXiv.2404.08401","DOI":"10.48550\/arXiv.2404.08401"},{"key":"2_CR16","doi-asserted-by":"crossref","unstructured":"Hartley, R., Zisserman, A.: Multiple view geometry in computer vision (Chapter 3: Projective Geometry and Transformations of 3D), 2nd edn. Cambridge University Press, Cambridge (2003)","DOI":"10.1017\/CBO9780511811685"},{"key":"2_CR17","unstructured":"Hinum, K.: NVIDIA GeForce RTX 4050 laptop GPU benchmarks and specs. Notebookcheck. https:\/\/www.notebookcheck.net\/NVIDIA-GeForce-RTX-4050-Laptop-GPU-Benchmarks-and-Specs.675695.0.html. Accessed 28 Apr 2025"},{"key":"2_CR18","unstructured":"Hinum, K.: NVIDIA GeForce RTX 4060 laptop GPU benchmarks and specs. Notebookcheck. https:\/\/www.notebookcheck.net\/NVIDIA-GeForce-RTX-4060-Laptop-GPU-Benchmarks-and-Specs.675692.0.html. Accessed 28 Apr 2025"},{"key":"2_CR19","doi-asserted-by":"publisher","unstructured":"Homayounfar, N., Fidler, S., Urtasun, R.: Sports field localization via deep structured models. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4012\u20134020. IEEE, Honolulu (2017). https:\/\/doi.org\/10.1109\/CVPR.2017.427","DOI":"10.1109\/CVPR.2017.427"},{"key":"2_CR20","unstructured":"IFAB Law 1 - The Field of Play. https:\/\/www.theifab.com\/laws\/latest\/the-field-of-play\/#field-surface. Accessed 24 Mar 2025"},{"key":"2_CR21","doi-asserted-by":"publisher","unstructured":"Jiang, W., Gamboa Higuera, J.C., Angles, B., Sun, W., Javan, M., Yi, K.M.: Optimizing through learned errors for accurate sports field registration. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 201\u2013210. IEEE, Snowmass (2020). https:\/\/doi.org\/10.1109\/WACV45572.2020.9093581","DOI":"10.1109\/WACV45572.2020.9093581"},{"key":"2_CR22","unstructured":"Jocher, G.: Ultralytics YOLO documentation. https:\/\/docs.ultralytics.com\/modes\/train\/. Accessed 28 Apr 2025"},{"key":"2_CR23","unstructured":"Jocher, G., Qiu, J.: Ultralytics YOLO11 (Version 11.0.0) [Software]. https:\/\/github.com\/ultralytics\/ultralytics. Accessed 25 Apr 2025"},{"key":"2_CR24","doi-asserted-by":"publisher","unstructured":"Ma, H., Ding, X.: Robust automatic camera calibration in badminton court recognition. In: Proceedings of the 2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC), pp. 893\u2013898. IEEE, Dalian (2022). https:\/\/doi.org\/10.1109\/IPEC54454.2022.9777532","DOI":"10.1109\/IPEC54454.2022.9777532"},{"key":"2_CR25","doi-asserted-by":"publisher","first-page":"18427","DOI":"10.1007\/s11042-023-16145-8","volume":"83","author":"M Manafifard","year":"2024","unstructured":"Manafifard, M.: A review on camera calibration in soccer videos. Multimed Tools Appl. 83, 18427\u201318458 (2024). https:\/\/doi.org\/10.1007\/s11042-023-16145-8","journal-title":"Multimed Tools Appl."},{"key":"2_CR26","unstructured":"Munawar, R., Jocher, G., Noyce, M.: YOLO keypoint annotation format. Ultralytics Documentation. https:\/\/docs.ultralytics.com\/datasets\/pose\/. Accessed 28 Apr 2025"},{"key":"2_CR27","unstructured":"Munawar, R., Jocher, G.: YOLOv8 performance metrics. Ultralytics Documentation. https:\/\/docs.ultralytics.com\/models\/yolov8\/#performance-metrics. Accessed 28 Apr 2025"},{"key":"2_CR28","doi-asserted-by":"publisher","unstructured":"Nie, X., Chen, S., Hamid, R.: A robust and efficient framework for sports-field registration. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 1936\u20131944. IEEE, Virtual Event (2021). https:\/\/doi.org\/10.1109\/WACV48630.2021.00198","DOI":"10.1109\/WACV48630.2021.00198"},{"key":"2_CR29","doi-asserted-by":"publisher","unstructured":"Oo, Y.M., Jamsrandorj, A., Chao, V., Mun, K.R., Kim, J.: A residual attention-based EfficientNet homography estimation model for sports field registration. In: Proceedings of the 49th Annual Conference of the IEEE Industrial Electronics Society (IECON), pp. 1\u20137. IEEE, Singapore (2023). https:\/\/doi.org\/10.1109\/IECON51785.2023.10312494","DOI":"10.1109\/IECON51785.2023.10312494"},{"key":"2_CR30","unstructured":"Roboflow: football-field-detection dataset. Roboflow Universe. https:\/\/universe.roboflow.com\/roboflow-jvuqo\/football-field-detection-f07vi. Accessed 25 Apr 2025"},{"key":"2_CR31","doi-asserted-by":"publisher","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), pp. 234\u2013241. Springer, Munich (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"2_CR32","doi-asserted-by":"publisher","unstructured":"Shang, J.C., Chen, Y., Shafiee, M.J., Clausi, D.A.: Rink-agnostic hockey rink registration. In: Proceedings of the 6th International Workshop on Multimedia Content Analysis in Sports, pp. 73\u201381. ACM, Ottawa (2023). https:\/\/doi.org\/10.1145\/3606038.3616161","DOI":"10.1145\/3606038.3616161"},{"key":"2_CR33","doi-asserted-by":"publisher","unstructured":"Sha, L., Hobbs, J., Felsen, P., Wei, X., Lucey, P., Ganguly, S.: End-to-end camera calibration for broadcast videos. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA, pp. 13624\u201313633 (2020). https:\/\/doi.org\/10.1109\/CVPR42600.2020.01364","DOI":"10.1109\/CVPR42600.2020.01364"},{"key":"2_CR34","doi-asserted-by":"publisher","unstructured":"Sharma, R.A., Bhat, B., Ghandi, V., Jawahar, C.V.: Automated top view registration of broadcast football videos. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 305\u2013313. IEEE, Lake Tahoe (2018). https:\/\/doi.org\/10.1109\/WACV.2018.00040","DOI":"10.1109\/WACV.2018.00040"},{"key":"2_CR35","unstructured":"Skalski, P.: Camera calibration in sports with keypoints. Roboflow Blog. https:\/\/blog.roboflow.com\/camera-calibration-sports-computer-vision\/. Accessed 25 Apr 2025"},{"key":"2_CR36","unstructured":"Skalski, P.: Soccer field configuration script. GitHub. https:\/\/github.com\/roboflow\/sports\/blob\/main\/sports\/configs\/soccer.py. Accessed 27 Apr 2025"},{"key":"2_CR37","doi-asserted-by":"publisher","unstructured":"Theiner, J., Ewerth, R.: TVCalib: camera calibration for sports field registration in soccer. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 1166\u20131175. IEEE\/CVF, Waikoloa (2023). https:\/\/doi.org\/10.1109\/WACV56688.2023.00122","DOI":"10.1109\/WACV56688.2023.00122"},{"key":"2_CR38","doi-asserted-by":"publisher","unstructured":"Zhang, N., Izquierdo, E.: A high accuracy camera calibration method for sport videos. In: Proceedings of the 2021 International Conference on Visual Communications and Image Processing (VCIP), pp. 1\u201315. IEEE, Munich (2021). https:\/\/doi.org\/10.1109\/VCIP53242.2021.9675379","DOI":"10.1109\/VCIP53242.2021.9675379"},{"key":"2_CR39","doi-asserted-by":"publisher","unstructured":"Zhang, N., Izquierdo, E.: A fast and effective framework for camera calibration in sport videos. In: Proceedings of the IEEE International Conference on Visual Communications and Image Processing (VCIP), pp. 1\u20135. IEEE, Suzhou (2022). https:\/\/doi.org\/10.1109\/VCIP56404.2022.10008882","DOI":"10.1109\/VCIP56404.2022.10008882"},{"issue":"11","key":"2_CR40","doi-asserted-by":"publisher","first-page":"1330","DOI":"10.1109\/34.888718","volume":"22","author":"Z Zhang","year":"2000","unstructured":"Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. 22(11), 1330\u20131334 (2000). https:\/\/doi.org\/10.1109\/34.888718","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Lecture Notes in Computer Science","Sports Analytics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-06167-6_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,25]],"date-time":"2025-09-25T18:51:42Z","timestamp":1758826302000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-06167-6_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,26]]},"ISBN":["9783032061669","9783032061676"],"references-count":40,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-06167-6_2","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,26]]},"assertion":[{"value":"26 September 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ISACE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Sports Analytics Conference and Exhibition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shanghai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 September 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 September 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"isace2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/formal-analysis.com\/isace\/2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}