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Quantitative evaluation strategies for urban 3D model generation from remote sensing data

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Download CandGpaper.pdf1.66 MB
Author(s)
Truong-Hong, Linh 
Laefer, Debra F. 
Uri
http://hdl.handle.net/10197/7444
Date Issued
June 2015
Date Available
01T01:00:10Z June 2017
Abstract
Over the last decade, several automatic approaches have been proposed to reconstruct 3D building models from aerial laser scanning (ALS) data. Typically, they have been benchmarked with data sets having densities of less than 25 points/m2. However, these test data sets lack significant geometric points on vertical surfaces. With recent sensor improvements in airborne laser scanners and changes in flight path planning, the quality and density of ALS data have improved significantly. The paper presents quantitative evaluation strategies for building extraction and reconstruction when using dense data sets. The evaluation strategies measure not only the capacity of a method to detect and reconstruct individual buildings but also the quality of the reconstructed building models in terms of shape similarity and positional accuracy.
Sponsorship
Environmental Protection Agency
European Research Council
Science Foundation Ireland
Type of Material
Journal Article
Publisher
Elsevier
Journal
Computers & Graphics
Volume
49
Start Page
82
End Page
91
Copyright (Published Version)
2015 Elsevier
Keywords
  • LiDAR data

  • Aerial laser scanning...

  • Point cloud

  • Building detection

  • Building reconstructi...

  • Evaluation strategy

DOI
10.1016/j.cag.2015.03.001
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Owning collection
Civil Engineering Research Collection
Scopus© citations
45
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Feb 4, 2023
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