A Graph-Based Approach for 3D Building Model Reconstruction from Airborne LiDAR Point Clouds

Bin Wu,Shenjun Yao,Jianping Wu,Feng Zhao,Bailang Yu,Weiqing Mao,Qiusheng Wu

doi:10.3390/rs9010092

Abstract

3D building model reconstruction is of great importance for environmental and urban applications. Airborne light detection and ranging (LiDAR) is a very useful data source for acquiring detailed geometric and topological information of building objects. In this study, we employed a graph-based method based on hierarchical structure analysis of building contours derived from LiDAR data to reconstruct urban building models. The proposed approach first uses a graph theory-based localized contour tree method to represent the topological structure of buildings, then separates the buildings into different parts by analyzing their topological relationships, and finally reconstructs the building model by integrating all the individual models established through the bipartite graph matching process. Our approach provides a more complete topological and geometrical description of building contours than existing approaches. We evaluated the proposed method by applying it to the Lujiazui region in Shanghai, China, a complex and large urban scene with various types of buildings. The results revealed that complex buildings could be reconstructed successfully with a mean modeling error of 0.32 m. Our proposed method offers a promising solution for 3D building model reconstruction from airborne LiDAR point clouds.

Highlights

Accurate and timely updated three-dimensional (3D) building modelling is a critical component in environmental and modern urban information systems [1,2]
We aim to address the drawbacks identified above by employing the graph-based localized contour tree method [53] and bipartite graph-matching theory to reconstruct 3D building models directly from building contours
We propose a graph-based approach for modeling urban buildings from airborne light detection and ranging (LiDAR) point clouds

Summary

Introduction

Accurate and timely updated three-dimensional (3D) building modelling is a critical component in environmental and modern urban information systems [1,2]. An increasing number of applications, such as urban planning, training simulations, virtual tourism, real-time emergency response, personal navigation, and homeland security, require 3D building models as an input source [2,3,4,5,6]. The 3D building models provide quick access to the urban topography, human-made structures, and our surrounding environment. 3D reconstruction of buildings has become increasingly important and efficient 3D urban building model reconstruction methods have become a very active research domain in recent years [7,8]. 3D building models are built up manually by using a digital photogrammetric workstation [9]. Manual 3D processing is time-consuming and labor-intensive [4,10]

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Conclusion