Abstract
Modern technology is strongly associated with sports. A perfect example of machine learning in sports is a support of detection of specific events or situations. Such a problem is present in boxing, where boxers’ moves need to be precisely detected. However video analysis is labor intensive but may provide valuable information. The paper presents the problem of processing recordings of boxing boxers, in which the dynamics is at an extremely high level and some events last for fractions of seconds. Additionally, the competition is often watched by spectators blocking the view. The goal of this paper is to present accurate, precise and quick method of detecting the presence of pugilists in the ring. This will allow to evaluate and score the boxing fight later. To validate the experiment, relevant material had to be collected – the authors recorded real boxing bouts and prepared the complete training set. The proposed solution will be used to automatically filter-out uninteresting parts of footage, where boxers are not engaged in close-combats situation.
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Stefański, P., Kozak, J., Jach, T. (2022). The Problem of Detecting Boxers in the Boxing Ring. In: Szczerbicki, E., Wojtkiewicz, K., Nguyen, S.V., Pietranik, M., Krótkiewicz, M. (eds) Recent Challenges in Intelligent Information and Database Systems. ACIIDS 2022. Communications in Computer and Information Science, vol 1716. Springer, Singapore. https://doi.org/10.1007/978-981-19-8234-7_46
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DOI: https://doi.org/10.1007/978-981-19-8234-7_46
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