The development and utilization of urban underground space is an important way to solve the “great urban disease”. As one of the most important types of urban underground foundations, utility tunnels have become increasingly popular in municipal construction. The investigation of utility tunnels is a general task and three-dimensional laser scanning technology has played a significant role in surveying and data acquisition. However, three-dimensional laser scanning technology suffers from noise and occlusion in narrow congested utility tunnel spaces, and the acquired point clouds are imperfect; hence, errors and redundancies are introduced in the extracted geometric elements. The topology of reconstructed BIM objects cannot be ensured. Therefore, in this study, a hierarchical segmentation method for point clouds and a topology reconstruction method for building information model (BIM) objects in utility tunnels are proposed. The point cloud is segmented into facades, planes, and pipelines hierarchically. An improved mean-shift algorithm is proposed to extract wall line features and a local symmetry-based medial axis extraction algorithm is proposed to extract pipelines from point clouds. A topology reconstruction method that searches for the neighbor information of wall and pipeline centerlines and establishes collinear, perpendicular, and intersecting situations is used to reconstruct a topologically consistent 3D model of a utility tunnel. An experiment on the Guangzhou’s Nansha District dataset successfully reconstructed 24 BIM wall objects and 12 pipelines within the utility tunnel, verifying the efficiency of the method.
As the foundation for digitalization, building information modeling (BIM) technology has been widely used in the field of architecture, engineering, construction, and facility management (AEC/FM). Unmanned aerial vehicle (UAV) oblique photogrammetry and laser scanning have become increasingly popular data acquisition techniques for surveying buildings and providing original data for BIM modeling. However, the geometric and topological reconstruction of solid walls, which are among the most important architectural structures in BIM, is still a challenging undertaking. Due to noise and missing data in 3D point clouds, current research mostly focuses on segmenting wall planar surfaces from unstructured 3D point clouds and fitting the plane parameters without considering the thickness or 3D shape of the wall. Point clouds acquired only from the indoor space are insufficient for modeling exterior walls. It is also important to maintain the topological relationships between wall objects to meet the needs of complex BIM modeling. Therefore, in this study, a geometry and topology modeling method is proposed for solid walls in BIM based on photogrammetric meshes and laser point clouds. The method uses a kinetic space-partitioning algorithm to generate the building footprint and indoor floor plan. It classifies interior and exterior wall segments and infers parallel line segments to extract wall centerlines. The topological relationships are reconstructed and maintained to build wall objects with consistency. Experimental results on two datasets, including both photogrammetric meshes and indoor laser point clouds, exhibit more than 90% completeness and correctness, as well as centimeter-level accuracy of the wall surfaces.
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