Point Cloud Registration Algorithm Based on Bounded Rotation Angle

ZHAO Fu-qun; ZHOU Ming-quan; GENG Guo-hua

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Point Cloud Registration Algorithm Based on Bounded Rotation Angle

更新时间：2026-09-04

- Point Cloud Registration Algorithm Based on Bounded Rotation Angle
- Vol. 34, Issue 3, Pages: 46-49(2017)
- 作者机构：
  
  1. 西北大学信息科学与技术学院,陕西,西安,710127
  2. 咸阳师范学院机构教育科学学院,陕西,咸阳,712000
  3. 北京师范大学信息科学与技术学院,北京,100875
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2017
- 稿件说明：
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赵夫群, 周明全, 耿国华. 基于有界旋转角的点云配准算法[J]. 微电子学与计算机, 2017, 34(3): 46-49.

ZHAO Fu-qun, ZHOU Ming-quan, GENG Guo-hua. Point Cloud Registration Algorithm Based on Bounded Rotation Angle[J]. 2017, 34(3): 46-49.
赵夫群, 周明全, 耿国华. 基于有界旋转角的点云配准算法[J]. 微电子学与计算机, 2017, 34(3): 46-49. DOI：

ZHAO Fu-qun, ZHOU Ming-quan, GENG Guo-hua. Point Cloud Registration Algorithm Based on Bounded Rotation Angle[J]. 2017, 34(3): 46-49. DOI：

摘要

针对目前已有的三维点云配准算法不能很好地解决旋转角度变化较大的配准问题

提出一种基于有界旋转角的配准算法.首先根据刚体变换的低维性质将全局配准问题转化成区域配准问题

通过区域划分、区域配准、求解组合系数、求解刚体变换等四个基本步骤实现初始配准; 然后在基本ICP算法的基础上通过设置旋转角度的边界来改进算法

以达到精确配准的目的.实验结果表明

该算法具有精确、快速、鲁棒的特点

并能避免噪声和外点的干扰

适用范围更加广泛.

Abstract

In the paper

a registration algorithm based on bounded rotation angle is proposed to solve the problem of the existing 3D point cloud algorithm which cant complete registration with large rotation angle change. Firstly

the global registration is transformed into regional registration according to the low dimensional nature of the rigid body transformation

and it achieves initial registration through the four steps of region division

region registration

solving combination coefficient and solving rigid body transformation; Secondly

the basic ICP algorithm is improved by setting boundary for rotation angle to achieve fine registration. The experimental results show that the proposed algorithm in the paper is accurate

fast and robust

and it can avoid the interference of noises and outliers.

关键词

Keywords

references

Herrmann M, Otesteanu M, Otto M. Fast and robust point cloud matching based on EM-ICP prepositioning[C]//2012 10th International Symposium on Electronics and Telecommunications (ISETC). UK, Timisoara, 2012: 99-103.

Besl P J, McKay N D. A method for registration of 3-D shapes[J]. IEEE Trans. Pattern Anal. Mach. Intell, 1992, 14(2): 239-256. DOI: 239

戴静兰, 陈志杨, 叶修梓. ICP算法在点云配准中的应用[J]. 中国图象图形学报, 2007, 13(3): 517-521. DOI: 517

Nuchter A, Lingemann K, Hertzberg J. Cached kd tree search for ICP algorithms[C]//Sixth International Conference on 3-D Digital Imaging and Modeling. Quebec, Canada, 2007: 419-426.

杨现辉, 王惠南. ICP算法在3D点云配准中的应用研究[J]. 计算机仿真, 2010, 27(8): 235-238. DOI: 235

薛耀红, 梁学章, 马婷, 等. 扫描点云的一种自动配准方法[J]. 计算机辅助设计与图形学学报, 2011, 23(2): 223-231. DOI: 223

韩宝昌, 曹俊杰, 苏志勋. 一种区域层次上的自动点云配准算法[J]. 计算机辅助设计与图形学学报, 2015, 27(2): 313-319. DOI: 313

卫维恕, 罗笑南, 李峥. 基于水平集的扫描点云简化算法及在人体模型上的应用[J]. 计算机研究与发展, 2008, 45(9): 1605-1611. DOI: 1605

Zhang Chunjia, Du Shaoyi, Liu Juan. Robust 3D point set registration using iterative closest point algorithm with bounded rotation angle[J]. Signal Processing, 2016, 120(C): 777-788. DOI: 777

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