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基于独立成分分析的三维点云配准算法

Three-Dimensional Point Cloud Registration Based on Independent Component Analysis

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摘要

点云配准是三维建模过程中的关键问题之一, 快速高精度的配准是点云配准研究的重点。提出了一种利用独立成分分析(ICA)的点云配准方法, 通过对两组点云数据作ICA, 得到其独立分量、混合矩阵, 以及解混合矩阵。由于ICA存在模糊问题, 两点云的独立分量可能存在顺序和符号上的差异, 在F范数最小的优化准则下可以得到两独立分量的最优变换矩阵。进一步, 根据点云数据与独立分量之间的关系, 实现点云的精确配准。实验结果表明, 该算法配准速度快, 具有较高的配准精度。

Abstract

Point cloud registration is one of the key issues in the process of three-dimensional modeling. Fast and high precision registration is the focus of point cloud registration. A method of point cloud registration based on independent component analysis (ICA) is proposed. The independent components, mixing matrix and unmixing matrix are obtained after ICA of two point cloud. Because of the fuzzy problem of ICA, the independent components of the two point cloud may have the difference in the order and the symbol. The optimal transformation matrix of two independent components can be obtained under the optimization criterion of minimum F norm. Further, the accurate registration of point clouds is achieved based on the relationship between point cloud data and independent components. Experimental results show that the proposed algorithm has faster registration speed and higher registration accuracy.

Newport宣传-MKS新实验室计划
补充资料

中图分类号:TP391

DOI:10.3788/lop56.011203

所属栏目:仪器,测量与计量

基金项目:四川省重点研发项目(2018GZ0226)

收稿日期:2018-06-26

修改稿日期:2018-07-06

网络出版日期:2018-07-18

作者单位    点击查看

刘鸣:四川大学电气信息学院, 四川 成都 610065
舒勤:四川大学电气信息学院, 四川 成都 610065
杨赟秀:西南技术物理研究所, 四川 成都 610041
袁菲:西南技术物理研究所, 四川 成都 610041

联系人作者:舒勤(shuchin@163.com)

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引用该论文

Liu Ming,Shu Qin,Yang Yunxiu,Yuan Fei. Three-Dimensional Point Cloud Registration Based on Independent Component Analysis[J]. Laser & Optoelectronics Progress, 2019, 56(1): 011203

刘鸣,舒勤,杨赟秀,袁菲. 基于独立成分分析的三维点云配准算法[J]. 激光与光电子学进展, 2019, 56(1): 011203

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