3/2013 - 2 |
Automatic Building Extraction from Terrestrial Laser Scanning DataHAO, W. , WANG, Y. , NING, X. , ZHAO, M. , ZHANG, J. , SHI, Z. , ZHANG, X. |
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Author keywords
building extraction, point cloud segmentation, plane recognition, terrestrial laser scanning
References keywords
data(13), sensing(9), remote(9), photogrammetry(8), segmentation(6), laser(6), extraction(6), ransac(5), point(5), building(5)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2013-08-31
Volume 13, Issue 3, Year 2013, On page(s): 11 - 16
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2013.03002
Web of Science Accession Number: 000326321600002
SCOPUS ID: 84884962911
Abstract
The extraction of building from the huge amount of point clouds with different local densities, especially in the presence of random noisy points, is still a formidable challenge. In this paper, we present a complete strategy for building extraction from terrestrial laser scanning data. First, a novel segmentation method is proposed to facilitate the task of building extraction. The points are grouped based on the normals and the adjacency relationships. Second, the planar surfaces are recognized from the segmentation results based on the properties of the Gaussian image. Finally, the buildings are extracted from the urban point clouds based on a collection of characteristics of point cloud segments like shape, normal direction and topological relationship. Experimental results demonstrate that the proposed method can be used as a robust way to extract buildings from terrestrial laser scanning data. At the same time, the buildings are decomposed into several patches which lay a good foundation for building reconstruction. |
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[1] PointNAC: Copula-Based Point Cloud Semantic Segmentation Network, Deng, Chunyuan, Chen, Ruixing, Tang, Wuyang, Chu, Hexuan, Xu, Gang, Cui, Yue, Peng, Zhenyun, Symmetry, ISSN 2073-8994, Issue 11, Volume 15, 2023.
Digital Object Identifier: 10.3390/sym15112021 [CrossRef]
[2] A Novel Keep Zero as Zero Polar Correlation Technique for Mobile Robot Localization using LIDAR, SIDHARTHAN, R. K., KANNAN, R., SRINIVASAN, S., BALAS, M. M., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 16, 2016.
Digital Object Identifier: 10.4316/AECE.2016.04003 [CrossRef] [Full text]
[3] A multi‐scale plane‐detection method based on the Hough transform and region growing, Leng, Xiaoxu, Xiao, Jun, Wang, Ying, The Photogrammetric Record, ISSN 0031-868X, Issue 154, Volume 31, 2016.
Digital Object Identifier: 10.1111/phor.12145 [CrossRef]
[4] A Window Detection Algorithm for Remote Laser Gas Leakage Detection System, Dong, Xiaozhou, Li, Jiaying, Wu, Junxian, Liu, Juan, Procedia Computer Science, ISSN 1877-0509, Issue , 2020.
Digital Object Identifier: 10.1016/j.procs.2020.06.148 [CrossRef]
[5] Slice-Based Window Detection from Scene Point Clouds, Hao, Wen, Wang, Yinghui, Liang, Wei, Ning, Xiaojuan, Li, Ye, 2018 International Conference on Virtual Reality and Visualization (ICVRV), ISBN 978-1-5386-8497-9, 2018.
Digital Object Identifier: 10.1109/ICVRV.2018.00014 [CrossRef]
[6] Extraction of lattice openings of buildings from terrestrial LiDAR data, Susaki, Junichi, 2014 8th IAPR Workshop on Pattern Reconition in Remote Sensing, ISBN 978-1-4799-7276-0, 2014.
Digital Object Identifier: 10.1109/PRRS.2014.6914285 [CrossRef]
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