Automated Geometric Reconstruction of Partially Occluded Steel Elements from Terrestrial Laser Scanning Data

This paper presents a new approach for reconstructing the geometric properties of steel members in bridges, such as steel girders, cross-frame members, and steel piles, by exploiting point clouds captured by terrestrial laser scanners. The key innovation is focused on automatically addressing the occlusions in the point clouds by leveraging a 3D occlusion labeling algorithm and parametric models. Through the 3D occlusion labeling algorithm, the spaces that are not occupied by the acquired point clouds are automatically labeled as empty spaces and occluded spaces, depending on whether they have been visited by the laser beams. By integrating this information with parametric models, the complete geometric properties of the steel elements can be effectively and automatically retrieved, even with a high level of occlusion. The effectiveness of the proposed approach is validated through preliminary experiments conducted on the steel girders in a highway bridge, and the accuracy is evaluated by comparing the computed geometric properties with that from ground-truth measurements.