Interdisciplinary Perspectives on Intangible Cultural Heritage Digitization: A Review of Vision-Based Human Pose Estimation Research

Zixuan Lu; Mingyuan Guo

doi:10.54097/sqjqd585

Authors

Zixuan Lu
Mingyuan Guo

DOI:

https://doi.org/10.54097/sqjqd585

Keywords:

Intangible cultural heritage(ICH); Human Pose Estimation(HPE)

Abstract

The digitization of intangible cultural heritage (ICH) has emerged as a pivotal direction for cultural preservation and transmission. Among enabling technologies, human pose estimation offers critical support for digitally documenting and disseminating performance-based ICH, such as Tai Chi and traditional dances. This paper systematically reviews the applications, technical challenges, and future trends of computer vision-based human pose estimation in ICH digitization. First, we analyze the strategic significance of ICH digitization and the unique requirements for motion capture in performance-based ICH. Next, we trace the technological evolution from traditional sensor-based methods to deep learning-driven approaches, with a focus on the applicability of core techniques, including pose estimation algorithms and temporal modeling in ICH contexts. Subsequently, we identify persistent bottlenecks, such as occlusion by intricate costumes, low-quality archival footage processing, and cross-cultural semantic understanding of movements. Finally, we prospect future research directions, including lightweight models, immersive virtual-augmented teaching systems, and digital twins, while proposing a synergistic "technology-culture-industry" innovation framework to bolster the dynamic preservation and global dissemination of ICH. By bridging computer vision and cultural heritage studies, this work aims to advance interdisciplinary research and foster sustainable digital safeguarding of traditional culture.

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