Three-dimensional building façade segmentation and opening area detection from point clouds

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Title: Three-dimensional building façade segmentation and opening area detection from point clouds
Authors: Zolanvari, S. M. Iman
Laefer, Debra F.
Natanzi, Atteyeh S.
Permanent link: http://hdl.handle.net/10197/9476
Date: Sep-2018
Abstract: Laser scanning generates a point cloud from which geometries can be extracted, but most methods struggle to do this automatically, especially for the entirety of an architecturally complex building (as opposed to that of a single façade). To address this issue, this paper introduces the Improved Slicing Method (ISM), an innovative and computationally-efficient method for three-dimensional building segmentation. The method is also able to detect opening boundaries even on roofs (e.g. chimneys), as well as a building’s overall outer boundaries using a local density analysis technique. The proposed procedure is validated by its application to two architecturally complex, historic brick buildings. Accuracies of at least 86% were achieved, with computational times as little as 0.53 s for detecting features from a data set of 5.0 million points. The accuracy more than rivalled the current state of the art, while being up to six times faster and with the further advantage of requiring no manual intervention or reliance on a priori information.
Funding Details: European Research Council
Type of material: Journal Article
Publisher: Elsevier
Copyright (published version): 2018 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS)
Keywords: Point cloud segmentationFeature detectionThree-dimensional model reconstructionLight Detection and Ranging (LiDAR)Laser scanning
DOI: 10.1016/j.isprsjprs.2018.04.004
Language: en
Status of Item: Peer reviewed
Appears in Collections:Civil Engineering Research Collection

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