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Article

Pairwise Coarse Registration of Indoor Point Clouds Using 2D Line Features

1
College of Hydraulic Science and Engineering, Yangzhou University, Jiangyang Middle Road 131, Yangzhou 225009, China
2
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
3
College of Earth Sciences, Chengdu University of Technology, Erxianqiao Dongsan Road 1, Chengdu 610059, China
4
Faculty of Geomatics, East China University of Technology, Nanchang 330013, China
5
Key Laboratory for Digital Land and Resources of Jiangxi Province, East China University of Technology, Nanchang 330013, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2021, 10(1), 26; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10010026
Received: 26 October 2020 / Revised: 24 December 2020 / Accepted: 11 January 2021 / Published: 12 January 2021
(This article belongs to the Special Issue 3D Indoor Mapping and Modelling)
Registration is essential for terrestrial LiDAR (light detection and ranging) scanning point clouds. The registration of indoor point clouds is especially challenging due to the occlusion and self-similarity of indoor structures. This paper proposes a 4 degrees of freedom (4DOF) coarse registration method that fully takes advantage of the knowledge that the equipment is levelled or the inclination compensated for by a tilt sensor in data acquisition. The method decomposes the 4DOF registration problem into two parts: (1) horizontal alignment using ortho-projected images and (2) vertical alignment. The ortho-projected images are generated using points between the floor and ceiling, and the horizontal alignment is achieved by the matching of the source and target ortho-projected images using the 2D line features detected from them. The vertical alignment is achieved by making the height of the floor and ceiling in the source and target points equivalent. Two datasets, one with five stations and the other with 20 stations, were used to evaluate the performance of the proposed method. The experimental results showed that the proposed method achieved 80% and 63% successful registration rates (SRRs) in a simple scene and a challenging scene, respectively. The SRR in the simple scene is only lower than that of the keypoint-based four-point congruent set (K4PCS) method. The SRR in the challenging scene is better than all five comparison methods. Even though the proposed method still has some limitations, the proposed method provides an alternative to solve the indoor point cloud registration problem. View Full-Text
Keywords: indoor point clouds; registration; 4DOF; line matching indoor point clouds; registration; 4DOF; line matching
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MDPI and ACS Style

Li, Z.; Zhang, X.; Tan, J.; Liu, H. Pairwise Coarse Registration of Indoor Point Clouds Using 2D Line Features. ISPRS Int. J. Geo-Inf. 2021, 10, 26. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10010026

AMA Style

Li Z, Zhang X, Tan J, Liu H. Pairwise Coarse Registration of Indoor Point Clouds Using 2D Line Features. ISPRS International Journal of Geo-Information. 2021; 10(1):26. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10010026

Chicago/Turabian Style

Li, Zhen, Xiaoming Zhang, Junxiang Tan, and Hua Liu. 2021. "Pairwise Coarse Registration of Indoor Point Clouds Using 2D Line Features" ISPRS International Journal of Geo-Information 10, no. 1: 26. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10010026

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