Pushup Counting and Evaluating Based on Human Keypoint Detection

Thinh Nguyen Truong, Nham Nguyen Xuan, Trung Nguyen Quoc, Vinh Truong Hoang
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Abstract

In recent years, the fitness industry has undergone significant expansion, with a significant percentage of the population adamantly refusing to give up their weekly training sessions. The growth of this industry has been accompanied by a rise in the services given by gyms and sports organisations, with user-centric planning and management systems for more technological sports activities. The mix of fitness and technology was already a burgeoning phenomenon, which has expanded further as a result of COVID-19. During the quarantine, though, we may only exercise at home. This project serves as your personal trainer for at-home workouts. Using Deep Learning and Signal Processing, it will assist you in doing correct push-ups.
基于人体关键点检测的俯卧撑计数与评价
近年来,健身行业经历了显著的扩张,有相当一部分人坚决拒绝放弃每周的健身课程。这一行业的发展伴随着健身房和体育组织提供的服务的增加,以用户为中心的规划和管理系统为更多的技术体育活动提供服务。健身和科技的结合已经是一种新兴的现象,在新冠疫情的影响下,这种现象进一步扩大。在隔离期间,我们只能在家里锻炼。这个项目是你在家锻炼的私人教练。使用深度学习和信号处理,它将帮助你做正确的俯卧撑。
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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