摘要
针对三维点云中路灯自动提取的问题,利用无人机点云,提出一种基于样本匹配的路灯点云分层提取方法。该方法首先利用布料模拟滤波(CSF)算法将原始点云划分为灯头层、灯杆层和地面层,并进行分层聚类;然后利用样本匹配的方法提取灯杆点云;最后基于灯头点云到灯杆中心的相对位置约束,对灯头点云进行提取,从而完成整个路灯的提取。试验结果表明,在不同道路环境下,该方法路灯提取的准确率、完整率和F1值均不低于90%,可以实现对路灯的高效完整提取。
This paper addresses the automatic extraction of street lamps from 3Dpoint clouds using unmanned aerial vehicle(UAV)data,proposing a sample matching layered extraction method.Firstly,the original point cloud is divided into three layers:lamp head layer,lamp pole layer and ground layer by cloth simulation filtering(CSF)algorithm,and hierarchical clustering is carried out.Then,the point cloud of lamp pole is extracted by sample matching algorithm.Finally,based on the relative position constraint between the lamp head point cloud and the center of the lamp pole,the lamp head point cloud is extracted,thus completing the extraction of the whole street lamp.Our experimental results show that in different road environments,the correctness,completeness and F1indices of street lamps extracted by the proposed method are not less than 90%,which can achieve efficient and complete extraction of the street lamp.
作者
杨伟
程亮
朱大明
谌颂
段志鑫
杜思雨
于俊
庄启智
东野升鹍
Yang Wei;Cheng Liang;Zhu Daming;Chen Song;Duan Zhixin;Du Siyu;Yu Jun;Zhuang Qizhi;Dongye Shengkun(School of Land and Resources Engineering,Kunming University of Science and Technology,Kunming650093,Yunnan,China;School of Geography and Ocean Sciences,Nanjing University,Nanjing210023,Jiangsu,China)
出处
《应用激光》
CSCD
北大核心
2024年第3期214-222,共9页
Applied Laser
基金
国家自然科学基金项目
后勤科研重点项目(42001401)。
关键词
无人机点云
路灯提取
布料模拟滤波
欧式聚类
样本匹配
unmanned aerial vehicle point cloud
street lamp extraction
cloth simulation filter
european clustering
sample matching
