现代建筑物点云平面特征识别方法
The Plane Feature Recognition Method for Modern Building Point Cloud
王新静 1段晨鑫 1姚怡烨1
作者信息
- 1. 华北水利水电大学,河南 郑州 450046
- 折叠
摘要
[目的]基于现代建筑物点云数据面片特征,提出一种基于随机抽样一致算法的平面分割识别方法.[方法]该方法先利用三维格网划分来建立空间格网单元,再根据随机采样点来确定局部格网单元,通过随机机制来拟合平面模型,经过局部打分来确定候选模型集,利用法向约束和共面分割来解决过分割和欠分割的问题.[结果]采用该方法可获取当前最优模型和一致集,并完成点云分割.[结论]试验结果表明,该方法能对富有平面特征的建筑物进行有效分割.
Abstract
[Purposes]According to the patch characteristics of modern building point cloud data,a plane segmentation recognition method based on random sampling consistent algorithm is proposed in this pa-per.[Methods]In this method,the spatial grid element is established by three-dimensional grid divi-sion,and then the local grid element is determined according to the random sampling points,the plane model is fitted by random mechanism,and the candidate model set is determined by local scoring.Nor-mal constraints and coplanar segmentation are used to solve the problems of over-segmentation and in-sufficient segmentation.[Findings]Finally,the current optimal model and consistent set are obtained,and the point cloud segmentation can be completed.[Conclusions]The experimental results show that this method can segment the buildings with plane features effectively.
关键词
点云/分割/局部采样/一致集Key words
point cloud/segmentation/local sampling/consistent set引用本文复制引用
出版年
2024
NETL
NSTL
万方数据