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Slicing Method for curved façade and window extraction from point clouds
Author(s)
Date Issued
September 2016
Date Available
01T02:00:33Z March 2017
Abstract
Laser scanning technology is a fast and reliable method to survey structures. However, the automatic conversion of such data into solid models for computation remains a major challenge, especially where non-rectilinear features are present. Since, openings and the overall dimensions of the buildings are the most critical elements in computational models for structural analysis, this article introduces the Slicing Method as a new, computationally-efficient method for extracting overall façade and window boundary points for reconstructing a façade into a geometry compatible for computational modelling. After finding a principal plane, the technique slices a façade into limited portions, with each slice representing a unique, imaginary section passing through a building. This is done along a façade’s principal axes to segregate window and door openings from structural portions of the load-bearing masonry walls. The method detects each opening area’s boundaries, as well as the overall boundary of the façade, in part, by using a one-dimensional projection to accelerate processing. Slices were optimised as 14.3 slices per vertical metre of building and 25 slices per horizontal metre of building, irrespective of building configuration or complexity. The proposed procedure was validated by its application to three highly decorative, historic brick buildings. Accuracy in excess of 93% was achieved with no manual intervention on highly complex buildings and nearly 100% on simple ones. Furthermore, computational times were less than 3 sec for data sets up to 2.6 million points, while similar existing approaches required more than 16 hr for such datasets.
Sponsorship
European Research Council
Type of Material
Journal Article
Publisher
Elsevier
Journal
ISPRS Journal of Photogrammetry and Remote Sensing
Volume
119
Start Page
334
End Page
346
Copyright (Published Version)
2016 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS)
Language
English
Status of Item
Not peer reviewed
This item is made available under a Creative Commons License
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