Yoga practice doesn’t require costly equipment, and learners can teach themselves by watching online video tutorials. However, to keep the screen in view during practice, learners often disrupt their movement balance, which affects execution and hinders learning. Moreover, improper yoga postures may cause negative effects. This paper introduces a home-based self-practice yoga system using Mixed Reality (MR) technology and the OpenPose framework to address disrupted movement postures during yoga learning. By providing an instructor video interface that tracks the user’s head movements, the system helps users focus on both the screen and their physical movements without distraction. It overlays real-time captured full-body user postures with instructional videos, allowing users to visually compare their movements with standard postures and correct errors, thus addressing the lack of feedback during self-practice. Research shows that this design enables learners to perform technical movements more smoothly and accurately, demonstrating its wide applicability and high practicality.

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AlignMR: Design of a Home Yoga Self Learning System Based on MR Technology

  • Huangyiming Wu,
  • Tuotuo Yang,
  • Xiaona Ma

摘要

Yoga practice doesn’t require costly equipment, and learners can teach themselves by watching online video tutorials. However, to keep the screen in view during practice, learners often disrupt their movement balance, which affects execution and hinders learning. Moreover, improper yoga postures may cause negative effects. This paper introduces a home-based self-practice yoga system using Mixed Reality (MR) technology and the OpenPose framework to address disrupted movement postures during yoga learning. By providing an instructor video interface that tracks the user’s head movements, the system helps users focus on both the screen and their physical movements without distraction. It overlays real-time captured full-body user postures with instructional videos, allowing users to visually compare their movements with standard postures and correct errors, thus addressing the lack of feedback during self-practice. Research shows that this design enables learners to perform technical movements more smoothly and accurately, demonstrating its wide applicability and high practicality.