Premium
Hierarchical classification of pole‐like objects in mobile laser scanning point clouds
Author(s) -
Liu Rufei,
Wang Peng,
Yan Zhaojin,
Lu Xiushan,
Wang Minye,
Yu Jiayong,
Tian Maoyi,
Ma Xinjiang
Publication year - 2020
Publication title -
the photogrammetric record
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.638
H-Index - 51
eISSN - 1477-9730
pISSN - 0031-868X
DOI - 10.1111/phor.12307
Subject(s) - point cloud , ransac , azimuth , point (geometry) , computer science , artificial intelligence , laser scanning , computer vision , column (typography) , pattern recognition (psychology) , mathematics , geometry , laser , optics , physics , image (mathematics) , telecommunications , frame (networking)
For the classification of pole‐like objects (trees, lamp posts, traffic lights and traffic signs) in mobile laser scanning (MLS) point clouds, a hierarchical classification method is proposed. The method consists of three major steps. (1) The objects’ cylindrical column sections are detected based on the characteristics of arc‐like points using RANSAC after denoising. (2) These detected objects are roughly classified into trees and man‐made poles based on the azimuthal coverage of point clouds above the cylindrical column. (3) Eigenvalue analysis and the principal direction of the upper pole projections are used to differentiate lamp posts, traffic lights and traffic signs. Experimental analysis shows that the method can effectively identify different types of pole‐like objects.