A partial overlapping point cloud registration method based on dynamic feature matching

Hui DU; Changliang ZHENG; Chunyu MIAO; Xiaomeng ZHANG

doi:10.11959/j.issn.1000-0801.2021010

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A partial overlapping point cloud registration method based on dynamic feature matching

Research and Development | 更新时间：2024-06-05

- A partial overlapping point cloud registration method based on dynamic feature matching
- Telecommunications Science Vol. 37, Issue 4, Pages: 97-107(2021)
- 作者机构：
  
  1. 北京电子科技职业学院电信工程学院，北京 100176
  2. 杭州安恒信息技术股份有限公司，浙江杭州 310051
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2021010
  CLC： P237
- Published Online：2021-04，
  
  Published：20 April 2021
- 稿件说明：
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Hui DU, Changliang ZHENG, Chunyu MIAO, et al. A partial overlapping point cloud registration method based on dynamic feature matching[J]. Telecommunications science, 2021, 37(4): 97-107.
DOI：

Hui DU, Changliang ZHENG, Chunyu MIAO, et al. A partial overlapping point cloud registration method based on dynamic feature matching[J]. Telecommunications science, 2021, 37(4): 97-107. DOI： 10.11959/j.issn.1000-0801.2021010.

摘要

点云配准方法能够有效地完成对不同重叠率、不同规模点云间的配准，可确保三维重建模型的精度。针对该问题，提出一种动态特征匹配的部分重叠点云配准方法，首先基于欧氏距离分割法将点云分割为子点云；然后提取子点云特征，考虑到不同点云的规模不同，提取的特征规模也是不同的，提出利用动态时间规整算法（DTW）完成子点云间的映射；最后利用迭代配准算法求取拼接点云间的平移、旋转矩阵，利用该矩阵完成点云间的配准和拼接。实验结果表明，提出的方法能够有效地解决部分重叠点云和不同规模点云的配准问题。

Abstract

The point cloud registration method can effectively complete the registration of point clouds with different overlap rates and various sizes

and ensure the accuracy of the 3D reconstruction model.To address the above issues

a partial overlapping point cloud registration method based on dynamic feature matching named PPCR was proposed.Firstly

the point cloud was divided into sub-point clouds based on the Euclidean distance segmentation method.Secondly

the features of sub-point clouds were extracted.Since the sizes of different point clouds are varied

the scales of the extracted features are also different.Thus

a dynamic time warping (DTW) algorithm was proposed to map the sub-point clouds.Finally

the registration algorithm was iterated to obtain the translation and rotation matrix between point clouds.This matrix was used to complete the registration and stitching between point clouds.Experimental results show that the proposed method can effectively solve the registration problems of partially overlapping point clouds and point clouds with different scales.

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