Reconstructing Buildings as Textured Low Poly Meshes from Point Clouds and Images

Abstract

Current urban building reconstruction techniques rely mainly on data gathered from either laser scans or image- based approaches, and do usually require a large amount of manual post-processing and modeling. Difficulties arise due to erroneous and noisy data, and due to the huge amount of information to process. We propose a system that helps to overcome these time-consuming steps by automatically generating low-poly 3D building models. This is achieved by taking both information from point clouds and image information into account, exploiting the particular strengths and avoiding the relative weaknesses of these data sources: While the segmented point cloud is used to identify the dominant planar surfaces in 3D space, the images are used to extract accurate edges, fill holes and generate textured polygonal meshes of urban buildings.