mlsanityData to 7 Oct 2026

Enhancing Sign Language Teaching: A Mixed Reality Approach for Immersive Learning and Multi-Dimensional Feedback

arXiv 2404.10490 ↗First posted 16 Apr 2024cs.CVcited by 1

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Abstract (arXiv)

Traditional sign language teaching methods face challenges such as limited feedback and diverse learning scenarios. Although 2D resources lack real-time feedback, classroom teaching is constrained by a scarcity of teacher. Methods based on VR and AR have relatively primitive interaction feedback mechanisms. This study proposes an innovative teaching model that uses real-time monocular vision and mixed reality technology. First, we introduce an improved hand-posture reconstruction method to achieve sign language semantic retention and real-time feedback. Second, a ternary system evaluation algorithm is proposed for a comprehensive assessment, maintaining good consistency with experts in sign language. Furthermore, we use mixed reality technology to construct a scenario-based 3D sign language classroom and explore the user experience of scenario teaching. Overall, this paper presents a novel teaching method that provides an immersive learning experience, advanced posture reconstruction, and precise feedback, achieving positive feedback on user experience and learning effectiveness.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 8 of its 23 references that are in the map. First posted on arXiv 16 Apr 2024.

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8 of 23 references.

References · 8

  1. 2016Realtime Multi-Person 2D Pose Estimation using Part Affinity Fieldscited by 1,061
  2. 2017Learning to Estimate 3D Hand Pose from Single RGB Imagescited by 234
  3. 2021FrankMocap: A Monocular 3D Whole-Body Pose Estimation System via Regression and Integrationcited by 168
  4. 2023One-Stage 3D Whole-Body Mesh Recovery with Component Aware Transformercited by 128
  5. 2019Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videoscited by 103
  6. 2018Video-based Sign Language Recognition without Temporal Segmentationcited by 88
  7. 2021SmoothNet: A Plug-and-Play Network for Refining Human Poses in Videoscited by 64
  8. 2017Using a single RGB frame for real time 3D hand pose estimation in the wildcited by 39

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