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Smartphone Application-Based Markerless Motion Capture and Biomechanical Analysis of Athletes using a Deep Learning Model

Smartphone Application-Based Markerless Motion Capture and Biomechanical Analysis of Athletes using a Deep Learning Model
使用深度学习模型对运动员进行基于智能手机应用的无标记动作捕捉和生物力学分析
批准号：
486618
负责人：
Attias Cedric
金额：
$1.27万
依托单位：
University of Waterloo (Ontario)
依托单位国家：
加拿大
项目类别：
Studentship Programs
财政年份：
2022
资助国家：
加拿大
项目状态：
已结题
起止时间：
2022-12-01 至 2023-12-01
来源：
https://webapps.cihr-irsc.gc.ca/decisions/p/project_details.html?applId=486618&lang=en
关键词：
Athletic Performance Biomechanical Analysis Deep Convolutional Neural Networks Deep Learning Injury Prevention Keypoint Estimation Markerless Motion Capture Motion Tracking Smartphone Application Technique

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英文摘要
To quantitatively assess athletic performance, motion capture (MC) technology can be leveraged to provide biomechanical feedback to athletes, coaches, and sports engineers. MC is the process of digitally encoding three-dimensional movements of objects, tr
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