Abstract
Shooting training system can help the shooters to enhance their performance. The objective of the proposed system is to design a cost-effective and environment friendly model. The system has two lasers, which are attached to the barrel of the gun and the camera. One laser is used to track the movement and another to detect the shot. The camera is used to record the training period of the shooter. After preprocessing, the shot is detected and the target is identified. The model gives the analysis of the shot by determining its position, calculating the score, tracking the movement of the gun and the time spent on the target in the different areas. The whole analysis is being plotted on the digital target, which is being formed according to the ISSF rules. Codes have been made publicly available at https://github.com/aman-kumar-jh/Smart-Shot.
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References
Ding P, Zhang X, Fan X, Cheng Q (2009) Design of automatic target-scoring system of shooting game based on computer vision. In: IEEE International Conference on Automation and Logistics, 2009, ICAL'09, pp 825–830. IEEE
Soetedjo A, Nurcahyo E (2011) Developing of low-cost vision-based shooting range simulator. Int J Comput Sci Network Secur 11(2):109–113
Guthe SA, Soni PM (2016) Target shooting training and instructive system model using python. In: International Journal of Engineering Research and Technology, pp 594–597
Rudzinski J, Luckner M (2012) Automatic scoring of shooting targets with tournament precision. In: KES, pp 324–334
Duda RO, Hart PE (1971)Â Use of the hough transformation to detect lines and curves in pictures. No. SRI-TN-36. Sri International Menlo Park CA Artificial Intelligence Center.
International Shooting Sport Federation, Official Statutes Rules and Regulation Sedition (2017)
Rongxin Du, Intelligent target scoring system based on image processing.
SCATT Company, Shooting training system user manual (SCATT MX–02)
Richard Pitcher, T (2015) An analysis of computer vision techniques to electronically score a rifle target. Rhodes University
SCATT Shooting Trainers. https://www.scatt.com/. Last accessed 20 Dec 2018
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Singha, J., Kumar, A. (2021). Vision-Based Smart Shot for Assisting Shooters. In: Patgiri, R., Bandyopadhyay, S., Balas, V.E. (eds) Proceedings of International Conference on Big Data, Machine Learning and Applications. Lecture Notes in Networks and Systems, vol 180. Springer, Singapore. https://doi.org/10.1007/978-981-33-4788-5_4
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DOI: https://doi.org/10.1007/978-981-33-4788-5_4
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