All-in-Net: Scorekeeping in Basketball Training using a Mobile Phone Camera and Image
DOI:
https://doi.org/10.4108/eetiot.9061Keywords:
Mobile Computing Systems and Applications, Smart training systems, Image recognitionAbstract
As basketball is one of the crowd's favorite invasion games, methods are being developed to enhance players' performance as technology improves. Recording large parts of training significantly reduces subjective training assessment compared to objective aspects. In this paper, basketball players and coaches use a mobile application based on image processing for achievements, measuring shooting the basket from different positions on the court and displaying feedback. The shooting technique and the percentage of success are measured using an algorithm that identifies the angle of the shot to the basket. The system monitors players' knowledge of results during training using one mobile phone camera. The paper describes the architecture and design of the mobile computing and application: Pre-training (define goals based on past performance and level of training difficulty), during training (data collection and compatible camera), and post-training (analysis and visualization of results). Finally, the paper discusses validation and implications.
Downloads
References
[1] B. FIBA, “International Basketball Federation (FIBA) - FIBA.basketball,” 2019. https://www.fiba.basketball/ (accessed Nov. 05, 2022).
[2] J. Young, “NBA 2021-2022 season: $10 billion revenue, TV viewership rebound?,” CNBC- Sports, 2021. https://www.cnbc.com/2021/10/18/nba-2021-2022-season-10-billion-revenue-tv-viewership-rebound.html (accessed Nov. 05, 2022).
[3] “$1.1 billion projected revenues for EuroLeague and its participating clubs in 2025-2026 - Eurohoops.” https://www.eurohoops.net/en/euroleague/847644/1-1-billion-projected-revenues-for-euroleague-and-its-participating-clubs-in-2025-2026/ (accessed Nov. 05, 2022).
[4] P. M. Fitts and M. I. Posner, “Human performance.,” 1967.
[5] C. A. Coker, Motor Learning and Control for Practitioners. Routledge, 2017. doi: 10.4324/9781315185613.
[6] S. J. Kim, M. Ogilvie, N. Shimabukuro, T. Stewart, and J. H. Shin, “Effects of Visual Feedback Distortion on Gait Adaptation: Comparison of Implicit Visual Distortion Versus Conscious Modulation on Retention of Motor Learning,” IEEE Trans. Biomed. Eng., vol. 62, no. 9, pp. 2244–2250, 2015, doi: 10.1109/TBME.2015.2420851.
[7] Michael D. Akers (Marquette University), Shaheen Wolff (Marquette University), and Thomas E. Buttross (Wayne University), “An Empirial Examination of the Factors Affecting the Success of NCAA Division I College Basketball Teams,” J. Bus. Econ. Stud., vol. 1, no. 2, pp. 57–70, Jan. 1992, Accessed: Nov. 05, 2022. [Online]. Available: https://epublications.marquette.edu/account_fac/72
[8] J. Pino-Ortega, D. Rojas-Valverde, C. D. Gómez-Carmona, and M. Rico-González, “Training design, performance analysis and talent identification—a systematic review about the most relevant variables through the principal component analysis in soccer, basketball and rugby,” International Journal of Environmental Research and Public Health, vol. 18, no. 5. pp. 1–18, 2021. doi: 10.3390/ijerph18052642.
[9] M. Rana and V. Mittal, “Wearable Sensors for Real-Time Kinematics Analysis in Sports: A Review,” IEEE Sens. J., vol. 21, no. 2, pp. 1187–1207, Jan. 2021, doi: 10.1109/JSEN.2020.3019016.
[10] P. R. Kamble, A. G. Keskar, and K. M. Bhurchandi, “Ball tracking in sports: a survey,” Artif. Intell. Rev., vol. 52, no. 3, pp. 1655–1705, Oct. 2019, doi: 10.1007/s10462-017-9582-2.
[11] B. T. Naik, M. F. Hashmi, and N. D. Bokde, “A Comprehensive Review of Computer Vision in Sports: Open Issues, Future Trends and Research Directions,” Appl. Sci., vol. 12, no. 9, p. 4429, Apr. 2022, doi: 10.3390/app12094429.
[12] I. Chistiyah and P. Priyanto, “Pengembangan Alat Bantu Latihan Shooting dengan Aplikasi My Basketball Coach Berbasis Android,” J. Sport Coach. Phys. Educ., vol. 6, no. 1, pp. 11–19, 2021, doi: 10.15294/jscpe.v6i1.45534.
[13] W. A. Adnan et al., “Development of BasketBall Coaching APP,” J. Phys. Conf. Ser., vol. 1489, no. 1, p. 012026, Mar. 2020, doi: 10.1088/1742-6596/1489/1/012026.
[14] Y. Acikmese, B. C. Ustundag, and E. Golubovic, “Towards an artificial training expert system for basketball,” in 2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017, 2017, vol. 2018-Janua, pp. 1300–1304. Accessed: Aug. 17, 2024. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/8266220/
[15] R. Aufan, O. Widianingsih, and M. Ihsan, “The Development Of Android Based Learning Media In Basketball Subject To Establish The Ability Of Fik Unimed Students,” Oct. 2019. doi: 10.4108/eai.18-10-2018.2287441.
[16] S. Shankar, R. P. Suresh, V. Talasila, and V. Sridhar, “Performance measurement and analysis of shooting form of basketball players using a wearable IoT system,” 2018. doi: 10.1109/CIMCA.2018.8739721.
[17] R. Metulini and M. Le Carre, “Measuring sport performances under pressure by classification trees with application to basketball shooting,” J. Appl. Stat., vol. 47, no. 12, pp. 2120–2135, Sep. 2020, doi: 10.1080/02664763.2019.1704702.
[18] G. Thomas, R. Gade, T. B. Moeslund, P. Carr, and A. Hilton, “Computer vision for sports: Current applications and research topics,” Comput. Vis. Image Underst., vol. 159, pp. 3–18, Jun. 2017, doi: 10.1016/j.cviu.2017.04.011.
[19] F. Cricri, S. Mate, I. D. D. Curcio, and M. Gabbouj, “Salient event detection in basketball mobile videos,” in Proceedings - 2014 IEEE International Symposium on Multimedia, ISM 2014, 2015, pp. 63–70. doi: 10.1109/ISM.2014.67.
[20] G. Bertasius, H. S. Park, S. X. Yu, and J. Shi, “Am i a Baller? Basketball Performance Assessment from First-Person Videos,” in Proceedings of the IEEE International Conference on Computer Vision, 2017, vol. 2017-Octob, pp. 2196–2204. doi: 10.1109/ICCV.2017.239.
[21] P. X. Liu, T. Y. Pan, H. S. Lin, H. K. Chu, and M. C. Hu, “BetterSight: Immersive Vision Training for Basketball Players,” in MM 2022 - Proceedings of the 30th ACM International Conference on Multimedia, Oct. 2022, pp. 6979–6981. doi: 10.1145/3503161.3547745.
[22] P. C. Wen, W. C. Cheng, Y. S. Wang, H. K. Chu, N. C. Tang, and H. Y. M. Liao, “Court Reconstruction for Camera Calibration in Broadcast Basketball Videos,” IEEE Trans. Vis. Comput. Graph., vol. 22, no. 5, pp. 1517–1526, 2016, doi: 10.1109/TVCG.2015.2440236.
[23] Z. Marquardt, J. Beira, N. Em, I. Paiva, and S. Kox, “Super Mirror: A Kinect Interface for Ballet Dancers,” in Conference on Human Factors in Computing Systems - Proceedings, 2012, vol. 2012-Janua, pp. 1619–1624. doi: 10.1145/2212776.2223682.
[24] A. Semeraro and L. Turmo Vidal, “Visualizing Instructions for Physical Training: Exploring Visual Cues to Support Movement Learning from Instructional Videos,” 2022. doi: 10.1145/3491102.3517735.
[25] H.-Y. Jo, L. Seidel, M. Pahud, M. Sinclair, and A. Bianchi, “FlowAR: How Different Augmented Reality Visualizations of Online Fitness Videos Support Flow for At-Home Yoga Exercises,” in Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023, pp. 1–17.
[26] R. Stanescu, “THE NEW ON COURT TENNIS SOFTWARE - PERSPECTIVES IN TRAINING PROCESS,” in 14th International Conference eLearning and Software for Education, 2018, vol. 3, no. 03, pp. 341–345. doi: 10.12753/2066-026x-18-192.
[27] C. J. Chao, C. W. Huang, C. J. Lin, H. H. Chu, and P. Huang, “DanceVibe: Assistive Dancing for the Hearing Impaired,” in EAI International Conference on Mobile Computing, Applications and Services (MobiCASE), 2018, pp. 21–39. doi: 10.1007/978-3-319-90740-6_2.
[28] Dantu, V. and Jonnada, S., 2012. Are You Burning Fat?. In Mobile Computing, Applications, and Services: Third International Conference, MobiCASE 2011, Los Angeles, CA, USA, October 24-27, 2011. Revised Selected Papers 3 (pp. 368-373). Springer Berlin Heidelberg.
[29] Yonit, R., Haim, E., Reut, L. and Roni, P., 2020. Safe Navigation by Vibrations on a Context-Aware and Location-Based Smartphone and Bracelet Using IoT. In Mobile Computing, Applications, and Services: 11th EAI International Conference, MobiCASE 2020, Shanghai, China, September 12, 2020, Proceedings 11 (pp. 121-133). Springer International Publishing.
[30] P. R. Kamble, A. G. Keskar, and K. M. Bhurchandi, “Ball tracking in sports: a survey,” Artif. Intell. Rev., vol. 52, no. 3, pp. 1655–1705, Oct. 2019, doi: 10.1007/S10462-017-9582-2/FIGURES/10.
[31] A. Edelmann-Nusser, A. Raschke, A. Bentz, S. Montenbruck, J. Edelmann-Nusser, and M. Lames, “Validation of Sensor-Based Game Analysis Tools in Tennis,” Int. J. Comput. Sci. Sport, vol. 18, no. 2, pp. 49–59, 2019, doi: 10.2478/ijcss-2019-0013.
[32] M. Straeten, P. Rajai, and M. J. Ahamed, “Method and implementation of micro Inertial Measurement Unit (IMU) in sensing basketball dynamics,” Sensors Actuators A Phys., vol. 293, pp. 7–13, Jul. 2019, doi: 10.1016/J.SNA.2019.03.042.
[33] R. Stănescu*, “The Role of Video Analysis Method in Tennis Performance,” Mar. 2018, pp. 277–282. doi: 10.15405/epsbs.2018.03.37.
[34] “Home | RSPCT Basketball.” https://www.rspctbasketball.com/ (accessed Jun. 28, 2023).
[35] R. Yonit, R. Amit, B. Mickael, B. Nikita, S. Lior, and B. Valotker, “Consumer-Oriented Web of Things Solution for Competitive Swimmers,” in Lecture Notes in Networks and Systems, 2022, vol. 283, pp. 1114–1127. doi: 10.1007/978-3-030-80119-9_75.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Yonit Rusho, Marcelo Sihman, Yeshayahu Huzler
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This is an open-access article distributed under the terms of the Creative Commons Attribution CC BY 3.0 license, which permits unlimited use, distribution, and reproduction in any medium so long as the original work is properly cited.
