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<p>The convergence of machine learning (ML) algorithms and artificial intelligence (AI) has sparked innovation in virtual reality (VR) platforms, attracting researchers across various fields. These technologies are harnessed to enhance dance performance through real-time feedback and analysis. Specifically, a VR platform tailored for Tai Chi practice has been developed, enabling learners to emulate coaches’ movements via virtual avatars. The system offers auxiliary tools like action decomposition and key point prompts to aid understanding. Feedback is provided based on posture accuracy, movement fluency, and speed control, guiding learners to refine their techniques. As learners mimic actions, real-time analysis of differences between their avatars and coaches’ avatars occurs until consistency is achieved. This integration of cutting-edge technologies aligns with the national focus on holistic education, particularly in sports dance. However, challenges arise in analyzing complex and repetitive movements in dance videos for precise retrieval. Factors like time sequence and granularity must be considered to select suitable video clips. This research sheds light on the vital role of ML and AI in advancing dance education and performance analysis within VR environments.</p>

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Investigating the application of computer VR technology and AI in the examination of dance movement patterns

  • 期刊论文

  • 发表日期：

    2025年5月2日

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  • Zhang Yue

摘要

The convergence of machine learning (ML) algorithms and artificial intelligence (AI) has sparked innovation in virtual reality (VR) platforms, attracting researchers across various fields. These technologies are harnessed to enhance dance performance through real-time feedback and analysis. Specifically, a VR platform tailored for Tai Chi practice has been developed, enabling learners to emulate coaches’ movements via virtual avatars. The system offers auxiliary tools like action decomposition and key point prompts to aid understanding. Feedback is provided based on posture accuracy, movement fluency, and speed control, guiding learners to refine their techniques. As learners mimic actions, real-time analysis of differences between their avatars and coaches’ avatars occurs until consistency is achieved. This integration of cutting-edge technologies aligns with the national focus on holistic education, particularly in sports dance. However, challenges arise in analyzing complex and repetitive movements in dance videos for precise retrieval. Factors like time sequence and granularity must be considered to select suitable video clips. This research sheds light on the vital role of ML and AI in advancing dance education and performance analysis within VR environments.