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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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building extraction, point cloud segmentation, plane recognition, terrestrial laser scanning
data(13), sensing(9), remote(9), photogrammetry(8), segmentation(6), laser(6), extraction(6), ransac(5), point(5), building(5)
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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
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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