An Improved Method for Power-Line Reconstruction from Point Cloud Data

被引:82
|
作者
Guo, Bo [1 ,2 ,3 ]
Li, Qingquan [1 ,2 ]
Huang, Xianfeng [4 ,5 ]
Wang, Chisheng [1 ,2 ,3 ]
机构
[1] Shenzhen Univ, Natl Adm Surveying Mapping & GeoInformat, Key Lab Geoenvironm Monitoring Coastal Zone, Nanhai Rd 3688, Shenzhen 518060, Peoples R China
[2] Shenzhen Univ, Shenzhen Key Lab Spatial Smart Sensing & Serv, Nanhai Rd 3688, Shenzhen 518060, Peoples R China
[3] Shenzhen Univ, Coll Civil Engn, Nanhai Rd 3688, Shenzhen 518060, Peoples R China
[4] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430072, Peoples R China
[5] Wuhan Univ, Collaborat Innovat Ctr Geospatial Technol, Wuhan 430072, Peoples R China
基金
美国国家科学基金会;
关键词
airborne laser scanning; power-line span; pylon; reconstruction; TRANSMISSION-LINES; CONTEXTUAL CLASSIFICATION; OBJECT RECOGNITION; LIDAR DATA; EXTRACTION; SEGMENTATION; REGISTRATION;
D O I
10.3390/rs8010036
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper presents a robust algorithm to reconstruct power-lines using ALS technology. Point cloud data are automatically classified into five target classes before reconstruction. In order to improve upon the defaults of only using the local shape properties of a single power-line span in traditional methods, the distribution properties of power-line group between two neighbor pylons and contextual information of related pylon objects are used to improve the reconstruction results. First, the distribution properties of power-line sets are detected using a similarity detection method. Based on the probability of neighbor points belonging to the same span, a RANSAC rule based algorithm is then introduced to reconstruct power-lines through two important advancements: reliable initial parameters fitting and efficient candidate sample detection. Our experiments indicate that the proposed method is effective for reconstruction of power-lines from complex scenarios.
引用
收藏
页数:17
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