虚拟现实中的动作捕捉系统回顾:提高运动训练的精确性

IF 1.8 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Xiaohui Li, Dongfang Fan, Junjie Feng, Yu Lei, Chao Cheng, Xiangnan Li
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引用次数: 0

摘要

在现代体育训练中,动作捕捉与虚拟现实(VR)之间的协同作用为提高训练精度提供了一种创新方法。这篇系统性综述深入探讨了运动捕捉在 VR 体育训练中的应用,强调了其变革潜力。通过全面的文献检索,我们研究了从增强体质到加速康复过程的各种应用。我们的研究结果强调了这种融合所提供的实时反馈、身临其境的训练环境和量身定制的训练方法的能力。然而,尽管前景广阔,硬件限制、数据处理复杂性和交互界面限制等挑战依然存在。未来的发展轨迹表明,人工智能和深度学习的影响会越来越大,有望带来更先进的硬件和更广泛的应用,包括小众体育学科。综述最后强调了更广泛的社会影响,建议向运动员整体健康方法转变。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Systematic review of motion capture in virtual reality: Enhancing the precision of sports training
In the modern era of sports training, the synergy between motion capture and Virtual Reality (VR) offers an innovative approach to enhancing training precision. This systematic review delves into the application of motion capture within VR for sports training, highlighting its transformative potential. Through a comprehensive literature search, we examined the myriad applications, from physical conditioning enhancements to accelerated rehabilitation processes. Our findings underscore the capability of real-time feedback, immersive training environments, and tailored regimes that this fusion provides. However, despite its promise, challenges such as hardware constraints, data processing complexities, and interaction interface limitations persist. Future trajectories indicate an increasing influence of AI and deep learning, promising more sophisticated hardware and a broader spectrum of applications, including niche sports disciplines. The review concludes with an emphasis on the wider societal implications, suggesting a shift towards a holistic athlete well-being approach.
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来源期刊
Journal of Ambient Intelligence and Smart Environments
Journal of Ambient Intelligence and Smart Environments COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
4.30
自引率
17.60%
发文量
23
审稿时长
>12 weeks
期刊介绍: The Journal of Ambient Intelligence and Smart Environments (JAISE) serves as a forum to discuss the latest developments on Ambient Intelligence (AmI) and Smart Environments (SmE). Given the multi-disciplinary nature of the areas involved, the journal aims to promote participation from several different communities covering topics ranging from enabling technologies such as multi-modal sensing and vision processing, to algorithmic aspects in interpretive and reasoning domains, to application-oriented efforts in human-centered services, as well as contributions from the fields of robotics, networking, HCI, mobile, collaborative and pervasive computing. This diversity stems from the fact that smart environments can be defined with a variety of different characteristics based on the applications they serve, their interaction models with humans, the practical system design aspects, as well as the multi-faceted conceptual and algorithmic considerations that would enable them to operate seamlessly and unobtrusively. The Journal of Ambient Intelligence and Smart Environments will focus on both the technical and application aspects of these.
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