Knowledge Management for Motion Capture and Visualization of Intangible Cultural Heritage Dance
Year: 2026
Type: article
Abstract: The inheritance of intangible cultural heritage (ICH) dances relies on oral transmission and demonstrations, which fail to preserve tacit movement knowledge. Video cannot capture joint angles, center-of-gravity shifts, or embedded semantics. This paper designs a motion capture and visualization system integrating multi-source acquisition, semantic mapping, and feedback writeback. Inertial nodes, depth cameras, and pressure plates enable synchronous calibration. Skeleton trajectories, rhythm deviations, and center-of-gravity shifts are decomposed into visual layers. Inheritor annotations and learner records are stored as writeback records for continuous updating. Results show skeleton fidelity exceeds 89 points across four dances. With 16 concurrent viewers, latency reaches 106 ms, exceeding the completeness threshold and indicating deployment limits. The capture + semantic scheme raises the median reproduction score to approximately 92 points. The core value lies in integrating capture accuracy, semantic interpretation, and knowledge management into a sustainable inheritance chain.
DOI: 10.4018/ijkm.420024
Authors: Shuran Xie, Li Xie
Institution: Yulin Normal University
Language: Ndonga
Topic: Human Motion and Animation
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7204207250