Multientity Registration of Point Clouds for Dynamic Objects on Complex Floating Platform Using Object Silhouettes

This article is focused on a challenging topic emerging from the registration of point clouds, specifically the registration of dynamic objects with low overlapping ratio. This problem is especially difficult when the static scanner is installed on a floating platform, and the objects it scans are a...

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Published in:IEEE transactions on geoscience and remote sensing Vol. 59; no. 1; pp. 769 - 783
Main Authors: Wang, Feng, Hu, Han, Ge, Xuming, Xu, Bo, Zhong, Ruofei, Ding, Yulin, Xie, Xiao, Zhu, Qing
Format: Journal Article
Language:English
Published: New York IEEE 01.01.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Cargo ships
Change detection
Floating
Floating platforms
Horizontal orientation
Iterative closest point algorithm
line matching
Marine vehicles
Merchant ships
Nonhomogeneous media
Object recognition
On-line systems
Planar structures
plane detection
point clouds registration
Regions
Registration
Robustness
terrestrial laser scanning
Three-dimensional displays
Urban environments
ISSN:0196-2892, 1558-0644
Online Access:Get full text
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Summary:This article is focused on a challenging topic emerging from the registration of point clouds, specifically the registration of dynamic objects with low overlapping ratio. This problem is especially difficult when the static scanner is installed on a floating platform, and the objects it scans are also floating. These issues make most of the automatic registration methods and software solutions invalid. To solve this problem, explicit exploration of the static region is necessary for both the coarse and fine registration steps. Fortunately, determining the corresponding regions can be eased by the intuitive realization that in urban environments, natural objects neither present straight boundaries nor stack vertically. This intuition has guided the authors to develop a robust approach for the detection of static regions using planar structures. Then, silhouettes of the objects are extracted from the planar structures, which assist in the determination of an SE(2) transformation in the horizontal direction by a novel line matching method. The silhouettes also enable identification of the correspondences of planes in the step of fine registration using a variant of the iterative closest point method. Experimental evaluations using point clouds of cargo ships with different sizes and shapes reveal the robustness and efficiency of the proposed method, which gives 100% success and reasonable accuracy in rapid time, suitable for an online system. In addition, the proposed method is evaluated systematically with regard to several practical situations caused by the floating platform, and it demonstrates good robustness to limited scanning time and noise.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2020.2995574