Digital restoration and feature recognition of a Qing-Dynasty vernacular dwelling based on multimodal data fusion.

ABSTRACT: This study addresses the urgent challenge of digitally preserving severely damaged vernacular architecture that lacks complete historical documentation. Taking the Dan Tao's Former Residence, a Qing Dynasty dwelling in the Jingchu region, as a case study, we propose a reproducible multimodal framework for reverse restoration. The approach integrates SLAM-based laser scanning, UAV photogrammetry, historical documentary evidence, analogy-driven HBIM construction, and knowledge-graph visualization. By bridging the semantic gaps between material remains, images, and textual records, the workflow enables high-fidelity digital modeling of complex components while decoding cultural features at multiple scales. Results demonstrate that the framework overcomes limitations of insufficient point-cloud density and missing documentation, achieving accurate 3D restoration of degraded structures and establishing a scalable cultural feature recognition system for Jingchu vernacular architecture. This research provides both methodological innovation and practical tools for conservation, offering a transferable paradigm for safeguarding endangered architectural heritage worldwide.

SUBMITTER: Xia X 

PROVIDER: S-EPMC12804802 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature