Towards Reconstructing 3D Buildings from ALS Data Based on Gestalt Laws

Pingbo Hu,Bisheng Yang,Hongchao Fan,Pengfei Yuan,Zhen Dong,Xuan Sun,Ronggang Huang

doi:10.3390/rs10071127

Abstract

3D building models are an essential data infrastructure for various applications in a smart city system, since they facilitate spatial queries, spatial analysis, and interactive visualization. Due to the highly complex nature of building structures, automatically reconstructing 3D buildings from point clouds remains a challenging task. In this paper, a Roof Attribute Graph (RAG) method is proposed to describe the decomposition and topological relations within a complicated roof structure. Furthermore, top-down decomposition and bottom-up refinement processes are proposed to reconstruct roof parts according to the Gestalt laws, generating a complete structural model with a hierarchical topological tree. Two LiDAR datasets from Guangdong (China) and Vaihingen (Germany) with different point densities were used in our study. Experimental results, including the assessment on Vaihingen standardized by the International Society for Photogrammetry and Remote Sensing (ISPRS), show that the proposed method can be used to model 3D building roofs with high quality results as demonstrated by the completeness and correctness metrics presented in this paper.

Highlights

Reconstruction of 3D building models has received intensive attention due to the demand for 3D building models in many applications related to urban planning and smart cities
Progress has been achieved in the 3D reconstruction of buildings, robust reconstructing of detailed 3D building models still face challenging issues due to input data quality issues, Level of Detail (LoD) requirements, the complexity of reconstructing structures, and the limited development of existing algorithms [6,13]
The main purpose of this paper is to introduce a new way to recognize and interpret 3D building models from a raw point cloud that combines meaningful structures, as expressed by a hierarchical topology tree

Summary

Introduction

Reconstruction of 3D building models has received intensive attention due to the demand for 3D building models in many applications related to urban planning and smart cities. Many of the methods and algorithms have been proposed and implemented to reconstruct 3D models using laser scanning point clouds and images with automated or interactive operators [1,2] in the field of photogrammetry and computer graphics [2,3,4,5,6,7], producing 3D building models at a city scale [8,9,10] and building scale [11,12]. Reconstructing of 3D buildings must meet the demanding requirements in both photo-realistic visualization and spatial computing. Existing 3D building reconstruction methods, struggle to meet the present requirements on visualization and spatial computing, and are still in the phase of development [14]

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