Title
Combined Rule-Based And Hypothesis-Based Method For Building Model Reconstruction From Photogrammetric Point Clouds
Abstract
Three-dimensional (3D) building models play an important role in digital cities and have numerous potential applications in environmental studies. In recent years, the photogrammetric point clouds obtained by aerial oblique images have become a major source of data for 3D building reconstruction. Aiming at reconstructing a 3D building model at Level of Detail (LoD) 2 and even LoD3 with preferred geometry accuracy and affordable computation expense, in this paper, we propose a novel method for the efficient reconstruction of building models from the photogrammetric point clouds which combines the rule-based and the hypothesis-based method using a two-stage topological recovery process. Given the point clouds of a single building, planar primitives and their corresponding boundaries are extracted and regularized to obtain abstracted building counters. In the first stage, we take advantage of the regularity and adjacency of the building counters to recover parts of the topological relationships between different primitives. Three constraints, namely pairwise constraint, triplet constraint, and nearby constraint, are utilized to form an initial reconstruction with candidate faces in ambiguous areas. In the second stage, the topologies in ambiguous areas are removed and reconstructed by solving an integer linear optimization problem based on the initial constraints while considering data fitting degree. Experiments using real datasets reveal that compared with state-of-the-art methods, the proposed method can efficiently reconstruct 3D building models in seconds with the geometry accuracy in decimeter level.
Year
DOI
Venue
2021
10.3390/rs13061107
REMOTE SENSING
Keywords
DocType
Volume
building models, 3D reconstruction, point clouds, photogrammetry
Journal
13
Issue
Citations 
PageRank 
6
0
0.34
References 
Authors
0
9
Name
Order
Citations
PageRank
Linfu Xie101.01
Han Hu211.36
Qing Zhu311.70
Xiaoming Li451760.22
Shengjun Tang534.46
You Li633.52
Renzhong Guo74111.41
Yeting Zhang801.01
Weixi Wang915.77