Automatic scoring in fencing by using skeleton points extracted from images

Takehiro Sawahata, Alessandro Moro, Sarthak Pathak, K. Umeda
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Abstract

First time spectators of fencing competitions cannot understand the complicated rules, making it difficult for them to enjoy the game. Therefore, in this paper, we propose a system that detects the situation of a fencing match using skeleton points extracted from videos. Players cannot be equipped with sensors or other devices to prevent interference with the match. Consequently, this research proposes a system that detects "phrases" using skeleton point information extracted from videos and displays the game situation. We evaluate actual videos of fencing to confirm the performance.
利用从图像中提取的骨架点进行击剑自动评分
第一次观看击剑比赛的观众无法理解复杂的规则,使他们很难享受比赛。因此,在本文中,我们提出了一种利用从视频中提取的骨架点来检测击剑比赛情况的系统。球员不能配备传感器或其他设备,以防止干扰比赛。因此,本研究提出了一个使用从视频中提取的骨架点信息来检测“短语”并显示游戏情境的系统。我们评估了实际的击剑视频来确认性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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