Historic Timber Roof Structure Reconstruction through Automated Analysis of Point Clouds

Area of Science:

• Heritage conservation
• Digital reconstruction
• 3D modeling

Background:

• Historic structures require detailed documentation for preservation.
• Terrestrial laser scanning (TLS) provides rich 3D data but requires extensive processing.
• Automating the modeling of complex historic roof structures remains a challenge.

Purpose of the Study:

• To develop and evaluate methods for improving the automation of parametric 3D modeling of historic roof structures.
• To increase the completeness of automatically generated 3D models from TLS point clouds.
• To refine point cloud processing for accurate structural element detection.

Main Methods:

• Applied a novel method to detect and exclude roof cover points from TLS data.
• Extended a region-growing segmentation approach for beam side face searching.
• Implemented a sub-segment splitting method for complex geometric features.
• Validated the workflow on an entire historic roof structure.

Main Results:

• Successfully excluded non-structural roof cover points.
• Enhanced segmentation accuracy for interior roof structure components.
• Increased the quantitative completeness of the automatically generated 3D model from 29% to 63%.
• Demonstrated the effectiveness of the integrated workflow on a real-world historic structure.

Conclusions:

• The presented methods significantly improve the automation and completeness of parametric 3D modeling for historic roofs.
• This approach offers a more efficient and accurate way to digitally preserve complex heritage structures.
• Further development can lead to near-complete automated 3D reconstruction of similar structures.