AI-Enhanced Multimodal Computational Modeling and Cross-Media Analytics for the Living Transmission of Fish-Skin Painting

DOI

10.2991/978-94-6239-737-8_37How to use a DOI?

Keywords

fish-skin painting; intangible cultural heritage; computational reconstruction; AI-assisted comparison; multimodal representation; cross-media communication

Abstract

Fish-skin painting is an important form of Hezhe intangible cultural heritage, yet its preservation faces challenges such as fragile materials, tacit manual skills, limited teaching resources, and geographically constrained exhibitions. This paper proposes an AI-assisted multimodal reconstruction framework integrating high-resolution image acquisition, 3D surface recording, process-video annotation, feature encoding, skill-comparison modeling, and cross-media deployment. Based on the Fuyuan case, the study analyzes more than 200 digitized works, records of 5 inheritors, over 2,000 student participants, 100,000+ annual visitors, 500,000+ livestream viewers, 80+ cultural creative products, and 50+ study-tour groups. Indicator calculation shows that the ratios of student participants to digitized works, livestream viewers to offline visitors, and cultural creative products to digitized works are about 10:1, 5:1, and 0.4:1, respectively. The results indicate that computational reconstruction can transform fragile craft objects and tacit knowledge into searchable, measurable, teachable, and reusable digital resources for the living transmission of fish-skin painting.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Zhaoli Wang
AU  - Lili Zhang
AU  - Jiahui Wang
AU  - Na Li
PY  - 2026
DA  - 2026/08/18
TI  - AI-Enhanced Multimodal Computational Modeling and Cross-Media Analytics for the Living Transmission of Fish-Skin Painting
BT  - Proceedings of the 2026 5th International Conference on Art Design and Digital Technology (ADDT 2026)
PB  - Atlantis Press
SP  - 296
EP  - 302
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6239-737-8_37
DO  - 10.2991/978-94-6239-737-8_37
ID  - Wang2026
ER  -