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

被引:51
作者
Zolanvari, S. M. Iman [1 ]
Laefer, Debra F. [1 ,2 ,3 ]
Natanzi, Atteyeh S. [1 ]
机构
[1] Univ Coll Dublin, Sch Civil Engn, Dublin, Ireland
[2] NYU, Tandon Sch Engn, Ctr Urban Sci & Progress, New York, NY USA
[3] NYU, Tandon Sch Engn, Dept Civil & Urban Engn, New York, NY USA
基金
欧洲研究理事会;
关键词
Point cloud segmentation; Three-dimensional model reconstruction; Feature detection; Light Detection and Ranging (LiDAR); Laser scanning; MODELS; ALGORITHMS; EXTRACTION; GENERATION;
D O I
10.1016/j.isprsjprs.2018.04.004
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
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 facade). 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. (C) 2018 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:134 / 149
页数:16
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