{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T06:53:03Z","timestamp":1776322383830,"version":"3.50.1"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T00:00:00Z","timestamp":1691712000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T00:00:00Z","timestamp":1691712000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001695","name":"Japan Science and Technology Corporation","doi-asserted-by":"publisher","award":["JPMJSP2125"],"award-info":[{"award-number":["JPMJSP2125"]}],"id":[{"id":"10.13039\/501100001695","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["20H04075"],"award-info":[{"award-number":["20H04075"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001695","name":"Japan Science and Technology Corporation","doi-asserted-by":"crossref","award":["JPMJPR20CA"],"award-info":[{"award-number":["JPMJPR20CA"]}],"id":[{"id":"10.13039\/501100001695","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Scientific Research Project of Higher Education Institutions of Anhui Province","award":["2022AH052181"],"award-info":[{"award-number":["2022AH052181"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The application of visual tracking to the performance analysis of sports players in dynamic competitions is vital for effective coaching. In doubles matches, coordinated positioning is crucial for maintaining control of the court and minimizing opponents\u2019 scoring opportunities. The analysis of such teamwork plays a vital role in understanding the dynamics of the game. However, previous studies have primarily focused on analyzing and assessing singles players without considering occlusion in broadcast videos. These studies have relied on discrete representations, which involve the analysis and representation of specific actions (e.g., strokes) or events that occur during the game while overlooking the meaningful spatial distribution. In this work, we present the first annotated drone dataset from top and back views in badminton doubles and propose a framework to estimate the control area probability map, which can be used to evaluate teamwork performance. We present an efficient framework of deep neural networks that enables the calculation of full probability surfaces. This framework utilizes the embedding of a Gaussian mixture map of players\u2019 positions and employs graph convolution on their poses. In the experiment, we verify our approach by comparing various baselines and discovering the correlations between the score and control area. Additionally, we propose a practical application for assessing optimal positioning to provide instructions during a game. Our approach offers both visual and quantitative evaluations of players\u2019 movements, thereby providing valuable insights into doubles teamwork. The dataset and related project code is available at <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/github.com\/Ning-D\/Drone_BD_ControlArea\">https:\/\/github.com\/Ning-D\/Drone_BD_ControlArea<\/jats:ext-link><\/jats:p>","DOI":"10.1007\/s11042-023-16362-1","type":"journal-article","created":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T08:02:41Z","timestamp":1691740961000},"page":"24777-24793","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Estimation of control area in badminton doubles with pose information from top and back view drone videos"],"prefix":"10.1007","volume":"83","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3067-7341","authenticated-orcid":false,"given":"Ning","family":"Ding","sequence":"first","affiliation":[]},{"given":"Kazuya","family":"Takeda","sequence":"additional","affiliation":[]},{"given":"Wenhui","family":"Jin","sequence":"additional","affiliation":[]},{"given":"Yingjiu","family":"Bei","sequence":"additional","affiliation":[]},{"given":"Keisuke","family":"Fujii","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,8,11]]},"reference":[{"key":"16362_CR1","doi-asserted-by":"crossref","unstructured":"Archana, M., Kalaiselvi\u00a0Geetha, M.: An efficient ball and player detection in broadcast tennis video. In: Intelligent Systems Technologies and Applications: Volume 1, pp. 427\u2013436 (2016). Springer","DOI":"10.1007\/978-3-319-23036-8_37"},{"key":"16362_CR2","doi-asserted-by":"crossref","unstructured":"Blank, P., Ho\u00dfbach, J., Schuldhaus, D., Eskofier, B.M.: Sensor-based stroke detection and stroke type classification in table tennis. In: Proceedings of the 2015 ACM International Symposium on Wearable Computers, pp. 93\u2013100 (2015)","DOI":"10.1145\/2802083.2802087"},{"key":"16362_CR3","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1007\/s10846-019-01114-x","volume":"99","author":"R Boutteau","year":"2020","unstructured":"Boutteau R, Rossi R, Qin L, Merriaux P, Savatier X (2020) A vision-based system for robot localization in large industrial environments. Journal of Intelligent & Robotic Systems 99:359\u2013370","journal-title":"Journal of Intelligent & Robotic Systems"},{"issue":"2","key":"16362_CR4","doi-asserted-by":"publisher","first-page":"355","DOI":"10.1177\/17479541211033078","volume":"17","author":"H Cho","year":"2022","unstructured":"Cho H, Ryu H, Song M (2022) Pass2vec: Analyzing soccer players\u2019 passing style using deep learning. International Journal of Sports Science & Coaching 17(2):355\u2013365","journal-title":"International Journal of Sports Science & Coaching"},{"issue":"1","key":"16362_CR5","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1109\/TVCG.2021.3114861","volume":"28","author":"X Chu","year":"2021","unstructured":"Chu X, Xie X, Ye S, Lu H, Xiao H, Yuan Z, Chen Z, Zhang H, Wu Y (2021) Tivee: Visual exploration and explanation of badminton tactics in immersive visualizations. IEEE Transactions on Visualization and Computer Graphics 28(1):118\u2013128","journal-title":"IEEE Transactions on Visualization and Computer Graphics"},{"key":"16362_CR6","unstructured":"Contributors, M.: OpenMMLab Pose Estimation Toolbox and Benchmark. https:\/\/github.com\/open-mmlab\/mmpose (2020)"},{"issue":"9","key":"16362_CR7","doi-asserted-by":"publisher","first-page":"15940","DOI":"10.1109\/TITS.2022.3146575","volume":"23","author":"K Dasgupta","year":"2022","unstructured":"Dasgupta K, Das A, Das S, Bhattacharya U, Yogamani S (2022) Spatio-contextual deep network-based multimodal pedestrian detection for autonomous driving. IEEE Transactions on Intelligent Transportation Systems 23(9):15940\u201315950","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"key":"16362_CR8","doi-asserted-by":"crossref","unstructured":"Deliege, A., Cioppa, A., Giancola, S., Seikavandi, M.J., Dueholm, J.V., Nasrollahi, K., Ghanem, B., Moeslund, T.B., Van\u00a0Droogenbroeck, M.: Soccernet-v2: A dataset and benchmarks for holistic understanding of broadcast soccer videos. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4508\u20134519 (2021)","DOI":"10.1109\/CVPRW53098.2021.00508"},{"key":"16362_CR9","doi-asserted-by":"publisher","first-page":"54764","DOI":"10.1109\/ACCESS.2022.3175314","volume":"10","author":"N Ding","year":"2022","unstructured":"Ding N, Takeda K, Fujii K (2022) Deep reinforcement learning in a racket sport for player evaluation with technical and tactical contexts. IEEE Access 10:54764\u201354772","journal-title":"IEEE Access"},{"key":"16362_CR10","doi-asserted-by":"publisher","unstructured":"Du, M., Yuan, X.: A survey of competitive sports data visualization and visual analysis. Journal of Visualization 24 (2020) https:\/\/doi.org\/10.1007\/s12650-020-00687-2","DOI":"10.1007\/s12650-020-00687-2"},{"key":"16362_CR11","doi-asserted-by":"crossref","unstructured":"Fern\u00e1ndez, J., Bornn, L.: Soccermap: A deep learning architecture for visually-interpretable analysis in soccer. In: Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track: European Conference, ECML PKDD 2020, Ghent, Belgium, September 14\u201318, 2020, Proceedings, Part V, pp. 491\u2013506 (2021). Springer","DOI":"10.1007\/978-3-030-67670-4_30"},{"key":"16362_CR12","unstructured":"Fernandez, J., Bornn, L.: Wide open spaces: A statistical technique for measuring space creation in professional soccer. In: Sloan Sports Analytics Conference, vol. 2018 (2018)"},{"key":"16362_CR13","doi-asserted-by":"crossref","unstructured":"Ghosh, A., Singh, S., Jawahar, C.: Towards structured analysis of broadcast badminton videos. In: 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 296\u2013304 (2018). IEEE","DOI":"10.1109\/WACV.2018.00039"},{"key":"16362_CR14","doi-asserted-by":"crossref","unstructured":"Giancola, S., Ghanem, B.: Temporally-aware feature pooling for action spotting in soccer broadcasts. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4490\u20134499 (2021)","DOI":"10.1109\/CVPRW53098.2021.00506"},{"key":"16362_CR15","unstructured":"Goldsberry, K.: Courtvision: New visual and spatial analytics for the nba. In: 2012 MIT Sloan Sports Analytics Conference, vol. 9, pp. 12\u201315 (2012)"},{"key":"16362_CR16","doi-asserted-by":"crossref","unstructured":"Haq, M.A., Tarashima, S., Tagawa, N.: Heatmap visualization and badminton player detection using convolutional neural network. In: 2022 International Electronics Symposium (IES), pp. 627\u2013631 (2022). IEEE","DOI":"10.1109\/IES55876.2022.9888717"},{"key":"16362_CR17","doi-asserted-by":"crossref","unstructured":"Hsu, T.-H., Chen, C.-H., Jut, N.P., Ik, T.-U., Peng, W.-C., Wang, Y.-S., Tseng, Y.-C., Huang, J.-L., Ching, Y.-T., Wang, C.-C., et al. Coachai: A project for microscopic badminton match data collection and tactical analysis. In: 2019 20th Asia-Pacific Network Operations and Management Symposium (APNOMS), pp. 1\u20134 (2019). IEEE","DOI":"10.23919\/APNOMS.2019.8893039"},{"key":"16362_CR18","doi-asserted-by":"crossref","unstructured":"Huang, Y.-C., Liao, I.-N., Chen, C.-H., \u0130k, T.-U., Peng, W.-C.: Tracknet: A deep learning network for tracking high-speed and tiny objects in sports applications. In: 2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), pp. 1\u20138 (2019). IEEE","DOI":"10.1109\/AVSS.2019.8909871"},{"issue":"3","key":"16362_CR19","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1007\/BF02289588","volume":"32","author":"SC Johnson","year":"1967","unstructured":"Johnson SC (1967) Hierarchical clustering schemes. Psychometrika 32(3):241\u2013254","journal-title":"Psychometrika"},{"key":"16362_CR20","doi-asserted-by":"publisher","first-page":"8055","DOI":"10.1109\/TIP.2020.3011269","volume":"29","author":"W Kim","year":"2020","unstructured":"Kim W, Kanezaki A, Tanaka M (2020) Unsupervised learning of image segmentation based on differentiable feature clustering. IEEE Transactions on Image Processing 29:8055\u20138068","journal-title":"IEEE Transactions on Image Processing"},{"key":"16362_CR21","doi-asserted-by":"crossref","unstructured":"Kulkarni, K.M., Shenoy, S.: Table tennis stroke recognition using two-dimensional human pose estimation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4576\u20134584 (2021)","DOI":"10.1109\/CVPRW53098.2021.00515"},{"key":"16362_CR22","doi-asserted-by":"crossref","unstructured":"Legg, P.A., Chung, D.H., Parry, M.L., Jones, M.W., Long, R., Griffiths, I.W., Chen, M.: Matchpad: interactive glyph-based visualization for real-time sports performance analysis. In: Computer Graphics Forum, vol. 31, pp. 1255\u20131264 (2012). Wiley Online Library","DOI":"10.1111\/j.1467-8659.2012.03118.x"},{"key":"16362_CR23","doi-asserted-by":"crossref","unstructured":"Lin, T.-Y., Goyal, P., Girshick, R., He, K., Doll\u00e1r, P.: Focal loss for dense object detection. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2980\u20132988 (2017)","DOI":"10.1109\/ICCV.2017.324"},{"key":"16362_CR24","doi-asserted-by":"crossref","unstructured":"Mueller, F., Bernard, F., Sotnychenko, O., Mehta, D., Sridhar, S., Casas, D., Theobalt, C.: Ganerated hands for real-time 3d hand tracking from monocular rgb. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 49\u201359 (2018)","DOI":"10.1109\/CVPR.2018.00013"},{"key":"16362_CR25","doi-asserted-by":"crossref","unstructured":"Perin, C., Vuillemot, R., Stolper, C.D., Stasko, J.T., Wood, J., Carpendale, S.: State of the art of sports data visualization. In: Computer Graphics Forum, vol. 37, pp. 663\u2013686 (2018). Wiley Online Library","DOI":"10.1111\/cgf.13447"},{"issue":"12","key":"16362_CR26","doi-asserted-by":"publisher","first-page":"2506","DOI":"10.1109\/TVCG.2013.192","volume":"19","author":"C Perin","year":"2013","unstructured":"Perin C, Vuillemot R, Fekete J-D (2013) Soccerstories: A kick-off for visual soccer analysis. IEEE transactions on visualization and computer graphics 19(12):2506\u20132515","journal-title":"IEEE transactions on visualization and computer graphics"},{"issue":"12","key":"16362_CR27","doi-asserted-by":"publisher","first-page":"2819","DOI":"10.1109\/TVCG.2012.263","volume":"18","author":"H Pileggi","year":"2012","unstructured":"Pileggi H, Stolper CD, Boyle JM, Stasko JT (2012) Snapshot: Visualization to propel ice hockey analytics. IEEE Transactions on Visualization and Computer Graphics 18(12):2819\u20132828","journal-title":"IEEE Transactions on Visualization and Computer Graphics"},{"issue":"12","key":"16362_CR28","doi-asserted-by":"publisher","first-page":"2339","DOI":"10.1109\/TVCG.2014.2346445","volume":"20","author":"T Polk","year":"2014","unstructured":"Polk T, Yang J, Hu Y, Zhao Y (2014) Tennivis: Visualization for tennis match analysis. IEEE transactions on visualization and computer graphics 20(12):2339\u20132348","journal-title":"IEEE transactions on visualization and computer graphics"},{"issue":"1","key":"16362_CR29","first-page":"397","volume":"26","author":"T Polk","year":"2019","unstructured":"Polk T, J\u00e4ckle D, H\u00e4u\u00dfler J, Yang J (2019) Courttime: Generating actionable insights into tennis matches using visual analytics. IEEE Transactions on Visualization and Computer Graphics 26(1):397\u2013406","journal-title":"IEEE Transactions on Visualization and Computer Graphics"},{"key":"16362_CR30","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-net: Convolutional networks for biomedical image segmentation. In: Medical Image Computing and Computer-Assisted Intervention\u2013MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III 18, pp. 234\u2013241 (2015). Springer","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"16362_CR31","doi-asserted-by":"crossref","unstructured":"Scott, A., Uchida, I., Onishi, M., Kameda, Y., Fukui, K., Fujii, K.: Soccertrack: A dataset and tracking algorithm for soccer with fish-eye and drone videos. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3569\u20133579 (2022)","DOI":"10.1109\/CVPRW56347.2022.00401"},{"key":"16362_CR32","unstructured":"Spearman, W., Basye, A., Dick, G., Hotovy, R., Pop, P.: Physics-based modeling of pass probabilities in soccer. In: Proceeding of the 11th MIT Sloan Sports Analytics Conference (2017)"},{"key":"16362_CR33","doi-asserted-by":"crossref","unstructured":"Voeikov, R., Falaleev, N., Baikulov, R.: Ttnet: Real-time temporal and spatial video analysis of table tennis. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 884\u2013885 (2020)","DOI":"10.1109\/CVPRW50498.2020.00450"},{"issue":"1","key":"16362_CR34","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1109\/TVCG.2019.2934630","volume":"26","author":"J Wang","year":"2019","unstructured":"Wang J, Zhao K, Deng D, Cao A, Xie X, Zhou Z, Zhang H, Wu Y (2019) Tac-simur: Tactic-based simulative visual analytics of table tennis. IEEE transactions on visualization and computer graphics 26(1):407\u2013417","journal-title":"IEEE transactions on visualization and computer graphics"},{"issue":"6","key":"16362_CR35","doi-asserted-by":"publisher","first-page":"2770","DOI":"10.1109\/TVCG.2021.3074576","volume":"27","author":"J Wang","year":"2021","unstructured":"Wang J, Wu J, Cao A, Zhou Z, Zhang H, Wu Y (2021) Tac-miner: Visual tactic mining for multiple table tennis matches. IEEE Transactions on Visualization and Computer Graphics 27(6):2770\u20132782","journal-title":"IEEE Transactions on Visualization and Computer Graphics"},{"issue":"23","key":"16362_CR36","doi-asserted-by":"publisher","first-page":"5230","DOI":"10.3390\/s19235230","volume":"19","author":"N Wawrzyniak","year":"2019","unstructured":"Wawrzyniak N, Hyla T, Popik A (2019) Vessel detection and tracking method based on video surveillance. Sensors 19(23):5230","journal-title":"Sensors"},{"issue":"1","key":"16362_CR37","doi-asserted-by":"publisher","first-page":"709","DOI":"10.1109\/TVCG.2017.2744218","volume":"24","author":"Y Wu","year":"2017","unstructured":"Wu Y, Lan J, Shu X, Ji C, Zhao K, Wang J, Zhang H (2017) ittvis: Interactive visualization of table tennis data. IEEE transactions on visualization and computer graphics 24(1):709\u2013718","journal-title":"IEEE transactions on visualization and computer graphics"},{"key":"16362_CR38","doi-asserted-by":"crossref","unstructured":"Yeh, R.A., Schwing, A.G., Huang, J., Murphy, K.: Diverse generation for multi-agent sports games. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4610\u20134619 (2019)","DOI":"10.1109\/CVPR.2019.00474"},{"key":"16362_CR39","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Sun, P., Jiang, Y., Yu, D., Weng, F., Yuan, Z., Luo, P., Liu, W., Wang, X.: Bytetrack: Multi-object tracking by associating every detection box. In: Computer Vision\u2013ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23\u201327, 2022, Proceedings, Part XXII, pp. 1\u201321 (2022). Springer","DOI":"10.1007\/978-3-031-20047-2_1"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-16362-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-023-16362-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-16362-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,22]],"date-time":"2024-02-22T13:32:01Z","timestamp":1708608721000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-023-16362-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,11]]},"references-count":39,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2024,3]]}},"alternative-id":["16362"],"URL":"https:\/\/doi.org\/10.1007\/s11042-023-16362-1","relation":{},"ISSN":["1573-7721"],"issn-type":[{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,11]]},"assertion":[{"value":"23 May 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 July 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 July 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 August 2023","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and\/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study received approval from the ethics committee at Anhui Normal University (No. AHNU-ET2022042) on April 14th, 2022, and all participants provided signed informed consent.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Standards"}},{"value":"The authors declare that they have no conflict of interest.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interest"}}]}}