A Movement Analysis Application using Human Pose Estimation and Action Correction

Gisela Miranda Difini, M. G. Martins, J. Barbosa
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引用次数: 1

Abstract

Human pose estimation (HPE) is an important field of computer vision that aims to predict poses of individuals from videos and images. It has been used in many different areas including human-computer interaction, motion analysis, surveillance, action prediction, action correction, augmented reality, virtual reality, and healthcare. Executing movements correctly is crucial in all kinds of physical activities, both to increase performance and reduce risk of injury. HPE is poised to help athletes better analyse the quality of their movements. This work proposes a model for movement analysis, repetition count, and movement correction in physical exercises using HPE. For this purpose, a study is carried out in the field of HPE applied to sports and another study is focused on HPE for correction and postural analysis. From this, it is verified what is the state of the art in HPE for physical exercises and what is the best method for analyzing movements. This work implements an application with improvements in respect to other related work, focusing mainly on the feedback presented to the user when performing a certain movement. To validate the proposed model, a quantitative research was carried out using the Unified Theory of Acceptance and Use (UTAUT). For both people who exercise and professionals in the field of physical education, the results demonstrate that the application is able to analyze the biomechanics of movement, responding with speed and precision to execution errors. Among other results are: user satisfaction, interest in using the application in the future, and agreement in relation to good performance in helping and analyzing physical exercises.
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基于人体姿态估计和动作校正的运动分析应用
人体姿态估计(HPE)是计算机视觉的一个重要领域,旨在从视频和图像中预测个体的姿态。它已被用于许多不同的领域,包括人机交互、运动分析、监视、动作预测、动作纠正、增强现实、虚拟现实和医疗保健。在各种体育活动中,正确地执行动作是至关重要的,既可以提高表现,又可以减少受伤的风险。惠普准备帮助运动员更好地分析他们的动作质量。这项工作提出了一个模型的运动分析,重复计数和运动纠正在体育锻炼中使用HPE。为此,一项研究是HPE在运动中的应用,另一项研究是HPE在矫正和姿势分析方面的应用。由此,验证了HPE体育锻炼的现状,以及分析运动的最佳方法。这项工作实现了一个应用程序,在其他相关工作的基础上进行了改进,主要关注在执行某个动作时呈现给用户的反馈。为了验证所提出的模型,使用统一接受和使用理论(UTAUT)进行了定量研究。对于锻炼者和体育教育领域的专业人士来说,结果表明该应用程序能够分析运动的生物力学,对执行错误做出快速和精确的反应。其他结果包括:用户满意度,未来使用应用程序的兴趣,以及在帮助和分析体育锻炼方面表现良好的一致性。
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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