Title
Fast Regularity-Constrained Plane Reconstruction.
Abstract
Man-made environments typically comprise planar structures that exhibit numerous geometric relationships, such as parallelism, coplanarity, and orthogonality. Making full use of these relationships can considerably improve the robustness of algorithmic plane reconstruction of complex scenes. This research leverages a constraint model requiring minimal prior knowledge to implicitly establish relationships among planes. We introduce a method based on energy minimization to reconstruct the planes consistent with our constraint model. The proposed algorithm is efficient, easily to understand, and simple to implement. The experimental results show that our algorithm successfully reconstructs planes under high percentages of noise and outliers. This is superior to other state-of-the-art regularity-constrained plane reconstruction methods in terms of speed and robustness.
Year
Venue
DocType
2019
arXiv: Computer Vision and Pattern Recognition
Journal
Volume
Citations 
PageRank 
abs/1905.07922
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Yangbin Lin1655.11
Jonathan Li2798119.18
Cheng Wang311829.56
Zhonggui Chen4746.16
Zongyue Wang500.68
Jonathan Li631.09