期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2009
卷号：XXXVIII-3/W8
页码：105-110
出版社：Copernicus Publications
摘要：The safety of powerline infrastructure significantly affects our everyday life and industrial activities. There are many factors and ob- jects to threaten powerline safety, which include encroaching vegetation, tree healthiness, ambient temperature of the powerlines, structural faults of insulator and tower and so on. A timely and accurate monitoring of those key powerline features enables to pre- vent causing possible dangerous situation such as blackout. At present, most of utility firms heavily rely on men-centric powerline monitoring methods which are time consuming and very costly, and also, hazardous work. Recently, airborne LiDAR system was in- troduced as a cost effective data acquisition tool which enables to rapidly capture 3D powerline scene with up to about 30 points/m 2 . This dramatically increased point density would provide a great possibility for achieving the automation of 3D reconstruction of po- werline scene features which is an essential step for a machine-based powerline safety monitoring. Since it has been lately used for the powerline monitoring, not many automatic algorithms for reconstructing powerline have been introduced using LiDAR data. This paper introduces a Voxel-based Piece-wise Line Detector (VPLD) which automatically reconstructs 3D powerline models using air- borne LiDAR data. The VPLD is developed based on well-known perceptual grouping framework which reconstructs a powerline by grouping similar features at different levels of information (i.e., points, segments and lines). A final reconstruction of single power- line models is accomplished by applying a non-linear adjustment for estimating catenary line parameters to a piece-wisely segmented voxel space. An evaluation of the proposed approach over a complicated powerline scene shows that the proposed method is promis- ing
