虚拟自卫教练-分析和得分用户的姿势

Aiman Khan, Muhammad Haris, Syed Sameer Nadeem, Samana Batool, Basit Memon, W. Saleem
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引用次数: 0

摘要

自卫是一项重要的自我安全技能,尤其是在危险时刻对妇女来说。然而,许多人无法接受自卫训练。本文提出了一个框架,该框架使用网络摄像头和openpose来估计人体姿势,并分析姿势,以便给出基于分数和性能的评论。该框架旨在向用户传授自卫技能。这个想法是通过RGB相机捕捉用户的姿势,并使用openpose估计姿势。然后提取特征并在时域内对齐姿态。整个管道的结果是每个提取特征的分数和自然语言反馈。结果表明,该系统在事先准备好的视频数据集上表现良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Virtual Self Defense Trainer - Analyzing and Scoring User Pose
Self-defence is an important skill for self safety especially for women in times of danger. However, self-defence training is not accessible to many. This paper presents a framework that estimates human pose using a webcam and openpose and analyzes the pose in order to give a score and performance based review. This framework aims at teaching self defense to users. The idea is to capture the pose of the user via an RGB camera and estimate pose using openpose. Then features are extracted and the poses aligned in the temporal domain. The result of the overall pipeline is a score and natural language feedback for each feature extracted. The results show that our system performs quite well on the video dataset prepared.
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