Automatic scoring in fencing by using skeleton points extracted from images

Takehiro Sawahata, Alessandro Moro, Sarthak Pathak, K. Umeda
{"title":"Automatic scoring in fencing by using skeleton points extracted from images","authors":"Takehiro Sawahata, Alessandro Moro, Sarthak Pathak, K. Umeda","doi":"10.1117/12.3000424","DOIUrl":null,"url":null,"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.","PeriodicalId":295011,"journal":{"name":"International Conference on Quality Control by Artificial Vision","volume":"100 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Quality Control by Artificial Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.3000424","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Single-camera multi-point vision: on the use of robotics for digital image correlation f-AnoGAN for non-destructive testing in industrial anomaly detection Object detection model-based quality inspection using a deep CNN Reducing the latency and size of a deep CNN model for surface defect detection in manufacturing Deep-learning based industrial quality control on low-cost smart cameras
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1