Three-dimensional (3D) reconstruction of structures and landscapes: A new point-and-line fusion method

被引:18
作者
Zhou, Ying [1 ]
Wang, Lingling [1 ]
Love, Peter E. D. [2 ]
Ding, Lieyun [1 ]
Zhou, Cheng [1 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Civil Engn & Mech, Wuhan 430074, Hubei, Peoples R China
[2] Curtin Univ, Sch Civil & Mech Engn, GPO Box U1987, Perth, WA 6845, Australia
基金
美国国家科学基金会;
关键词
3D reconstruction; Multi-view stereo; Depth-map propagation; Structure; Landscape; STRUCTURE-FROM-MOTION; MULTIVIEW STEREO; EFFICIENT; ALGORITHM; ACCURACY; CLOUD;
D O I
10.1016/j.aei.2019.100961
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The technique of three-dimensional (3D) reconstruction is widely used to develop infrastructure and landscape models to manage cities and assets better. Accurately reconstructing 3D structures (e.g., planes or lines) is a core step in rebuilding a model, especially within a built environment, where piece-wise planar/linear structures predominately prevail. As high-resolution images of large areas have become increasingly accessible, this paper develops an improved 3D reconstruction pipeline using the combination of point and line features. By introducing a dense reconstruction algorithm, which is an improved patch based stereo matching algorithm, this paper presents a robust approach that can be used to overcome the inaccuracies, integrity and reconstruction inefficiencies associated with point clouds. A 3D line extraction method is added to reconstruct accurate edges of buildings. The experimental results demonstrate that the proposed method visually improves the reconstruction effect of a 3D structure and a model's visualization.
引用
收藏
页数:11
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