Semi-automated reconstruction of HBIM from laser scan point clouds by integrating Scan-to-BIM and family library modeling

Despite advances in automated Building Information Modeling (BIM) reconstruction, existing methods remain unsuitable for complex historic buildings. This paper proposes a semi-automated reconstruction workflow that integrates the Scan-to-BIM workflow with family library modeling. The method combines region-growing and building semantics for point cloud segmentation, extracts modeling information from component characteristics, constructs parametric families through typological classification of complex elements, automatically filters door and window FamilySymbols via Revit secondary development, and assembles all components into a BIM model. Experiments show that the reconstructed model achieves a root mean square error (RMSE) of 0.039 m. When tolerance threshold τ = 0.25 m, completeness is 94.9% and correctness is 90.9%, demonstrating the reliability of the approach. The method improves automation in historic building documentation and enhances conventional Historic Building Information Modeling (HBIM) workflows. A limitation of this study is its single-case basis, which calls for additional validation across diverse heritage contexts.