Due to increasing traffic on roads and railways, the maintenance of bridges is becoming more and more important. Building Information Modelling (BIM) provides the perfect basis to efficiently plan these maintenance activities. However, for historic bridges, which moreover require intensive maintenance, there is no BIM available. The demand to digitize these bridges is correspondingly high. Further, to the already existing measurement methods (laser scanning, photogrammetry, etc.), a novel workflow for the digitalization of bridges from 2D plans is presented. Based on image processing for corner detection, 3D point cloud reconstruction of parts and fusion of reconstructed parts can be used create a 3D object to scale. The point cloud can serve as a supplement to as-built laser scanning or camera data. The presented method was evaluated based on three bridges over the Dreisam river in Freiburg, Germany.

Multiple viewpoint 3D reconstruction has been used in recent years to create accurate complete scenes and objects used for various applications. This is to overcome limitations of single viewpoint 3D digital imaging such as occlusion within the scene during the reconstruction process. In this paper, we propose a weighted point cloud fusion process using both local and global spatial information of the point clouds to fuse them together. The process aims to minimize duplication and remove noise while maintaining a consistent level of details using spatial information from point clouds to compute a weight to fuse them. The algorithm improves the overall accuracy of the fused point cloud while maintaining a similar degree of coverage comparable with state-of-the-art point cloud fusion algorithms.