Geometry and Topology Reconstruction of BIM Wall Objects from Photogrammetric Meshes and Laser Point Clouds

Author:

Yang Fan12ORCID,Pan Yiting1,Zhang Fangshuo1,Feng Fangyuan1,Liu Zhenjia1,Zhang Jiyi13,Liu Yu245,Li Lin5ORCID

Affiliation:

1. Nantong Key Laboratory of Spatial Information Technology R&D and Application, College of Geographic Science, Nantong University, Nantong 226019, China

2. Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen 518034, China

3. Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210046, China

4. Institute of Environment and Development, Guangdong Academy of Social Sciences, Guangzhou 510635, China

5. School of Resource and Environmental Sciences (SRES), Wuhan University, Wuhan 430079, China

Abstract

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.

Funder

Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources

National Natural Science Foundation of China

Introduction Program of High-Level Innovation and Entrepreneurship Talents in Jiangsu Province

Natural Science Foundation of Anhui Province

Key Lab of Virtual Geographic Environment Open Fund Project of the Ministry of Education

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

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