利用结构特征的点云快速配准算法  

Quick Registration Algorithm of Point Clouds Using Structure Feature

作　　者：王畅 舒勤[1] 杨赟秀[2] 陈蔚[2] Wang Chang;Shu Qin;Yang Yunxiu;Chen Wei(College of Electrical Engineering and Information Technology,Sichuan University,Chengdu,Sichuan 610065,China;Southwest Institute of Technical Physics,Chengdu,Sichuan 610041,China)

机构地区：[1]四川大学电气信息学院,四川成都610065 [2]西南技术物理研究所,四川成都610041

出　　处：《光学学报》2018年第9期167-174,共8页Acta Optica Sinica

基　　金：四川省重点研发项目(2018GZ0226)

摘　　要：为提高三维激光扫描点云的配准精度以及效率,解决数据点缺失、点云散乱时的配准问题,结合点云的全局和局部结构特征的不变特性,提出基于全局结构特征的初始配准算法和利用局部结构特征的快速精确配准算法。首先,给出全局结构特征的定义,并阐明初始配准方法,证明在点云样本集缺失数据时初始配准算法的有效性;然后,给定一种空间区域的划分方式,并找出划分的空间区域中两个点云的对应点;最后,通过找出的有限个对应点实现点云的精确配准。在仿真和实验数据处理时,该精确配准算法能够有效地完成缺失、散乱点云的精确、快速配准,且在效率和精度上比其他几种算法具有明显优势。To improve the registration of point clouds scanned by 3 Dlaser in terms of accuracy and efficiency,and solve the registration problems when data points are missing and out of order,based on the invariant characteristics of global and local structure features of point clouds,an initial registration algorithm using global structure features and a fast and accurate registration algorithm using local structure features are proposed.First,the global structure feature and the initial registration method are defined.The validity of the initial registration is strictly proved when the data point is lost.Then,we propose a way to partition the spatial region and find out the corresponding points of the two point clouds in the spatial region.Finally,the two clouds achieve precise registration through the corresponding points found.In the processes of simulation and experiment,the proposed algorithm can effectively perform accurate and rapid registration of missing and scattered point clouds.It has obvious advantages in efficiency and accuracy than other algorithms.

关 键 词：成像系统 图像配准 结构特征 最小二乘法 数据缺失 散乱点云 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]