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

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Title: Quantitative evaluation strategies for urban 3D model generation from remote sensing data
Authors: Truong-Hong, LinhLaefer, Debra F.
Permanent link: http://hdl.handle.net/10197/7444
Date: Jun-2015
Online since: 2017-06-01T01:00:10Z
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.
Funding Details: 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 dataAerial laser scanningPoint cloudBuilding detectionBuilding reconstructionEvaluation strategy
DOI: 10.1016/j.cag.2015.03.001
Language: en
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/
Appears in Collections:Earth Institute Research Collection
Civil Engineering Research Collection

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