摘要
针对三维点云配准中点云尺度不一致导致配准精确度不高的问题,提出基于几何重心和质心距离比不变性的多尺度点云配准算法。对点云进行滤波处理;通过点云数据重心与质心建立点云数据之间的尺度比例计算模型;根据配准误差与尺度真值函数关系,对尺度因子进行逐步细化,结合ICP算法进行配准。针对点云数据中不同的情况进行了对比实验,结果表明:在无噪声情况下,实验点云数据配准误差数量级为10^(–12)~10^(–15);在有噪声情况下,实验点云数据配准误差数量级为10^(–4)。
To address the low registration accuracy issue caused by scale mismatch of two point clouds, a multi-scale point cloud registration algorithm is proposed based on the distance ratio invariance of the geometric center of gravity and centroid. The point cloud is firstly filtered. Then, the scale ratio calculation model of the point cloud data is established by computing the point cloud＇s gravity center and centroid. Finally, according to the relationship between the registration error and the scale true value, the scale factor is refined step by step with ICP algorithm. For the noise and the inconsistent point in the point cloud, comparative tests are carried out. The experimental results show that, in the absence of noise, the magnitude of registration error order is 10^（–12）~10^（–15）; in the case with noise, the magnitude of registration error order is 10^（–4）.
作者
孙水发
李准
夏坤
施云飞
杨继全
董方敏
Sun Shuifa;Li Zhun;Xia Kun;Shi Yunfei;Yang Jiquan;Dong Fangmin(China Three Gorges University Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering, Yichang 443002 China;Nanjing Normal University Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing, Nanjing 210042, China)
出处
《系统仿真学报》
CAS
CSCD
北大核心
2018年第7期2465-2474,共10页
Journal of System Simulation
基金
国家自然科学基金(61273243)
湖北省自然科学基金创新群体项目(2015CFA025)
湖北省教育厅科学技术研究计划重点项目(D20151204)
关键词
多尺度
配准
重心
质心
噪声
multi-scale
point cloud registration
center of gravity
centroid
noise
