基于非均匀划分的机车走行部三维点云精简  

Simplification of locomotive running gear three-dimensional point cloud based on non-uniform division

作　　者：兰渐霞 王泽勇 李金龙 黄潜 高晓蓉 Lan Jianxia;Wang Zeyong;Li Jinlong;Huang Qian;Gao Xiaorong(Photoelectronic Engineering Institute,School of Physical Science and Technology,Southwest Jiaotong University,Chengdu,Sichuan 610031,China)

机构地区：[1]西南交通大学物理科学与技术学院光电工程研究所,四川成都610031

出　　处：《光电工程》2019年第2期25-33,共9页Opto-Electronic Engineering

基　　金：国家自然科学基金资助项目(61471304)~~

摘　　要：激光线结构光扫描仪得到的三维点云数据具有冗余性,本文设计实现了一种基于两阶非均匀划分的点云精简算法对机车走行部数据进行处理。首先,根据内在形状特征算法估计出检测对象的点云法矢,并提取出点云特征点;其次,根据特征点云的分布对点云进行第一次非均匀划分,得到不均匀的初始点云块;最后,将划分后的各点云块映射到不同的高斯球中进行进一步细分,在高斯球面上进行均值漂移聚类,提取出每个聚类簇在实际三维空间中的重心,重心的集合即为精简结果。实验证明了方法的有效性,相比于现有的方法,本文中的方法在保证精度的前提下能够达到很高的精简率和运算效率,更契合机车自动化在线检测的需要。The 3D point cloud data obtained from the laser line structured light scanner has redundancy,and a point cloud simplification algorithm based on the two order non-uniform partition is designed and implemented to deal with locomotive running department in this paper.First,according to the intrinsic shape signature(ISS),the point cloud normal vector of the detected object are estimated and the feature points of the point cloud are extracted.Then,according to the distribution of the feature point cloud,the point cloud is first divided non-uniformly to obtain uneven initial cloud patches.Finally,the divided cloud points are mapped to different Gaussian spheres for further subdivision.The mean shift clustering is performed on the Gauss sphere to extract the center of gravity of each cluster in the actual three-dimensional space.The set of the center of gravity is the result of simplification.Experimental results verified the effectiveness of the proposed method.It can keep the details information of the point cloud while ensuring a high simplification rate.Comparing with the existing method,this method balances the speed and accuracy,and is more suitable for the on-line locomotive automated detection system.

关 键 词：点云精简 非均匀划分 高斯映射 均值漂移 

分 类 号：TB872[一般工业技术—摄影技术] TP391.41[自动化与计算机技术—计算机应用技术]