面向缺失点云配准的镜像迭代最近点算法

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面向缺失点云配准的镜像迭代最近点算法

更新时间：2025-07-09

- 面向缺失点云配准的镜像迭代最近点算法
- Issue 7, Pages: 201-212+220(2023)
- 作者机构：
  
  西安交通大学软件学院
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391.41
- Published：2023
- 稿件说明：
移动端阅览
[J]. 2023, (7): 201-212+220.
DOI：

[J]. 2023, (7): 201-212+220. DOI：

摘要

面向点云配准任务，以改善重叠度较低的点云对之间的配准效果为研究目的，提出了一种有效的缺失点云配准算法——镜像迭代最近点算法。该算法以建立源点云和目标点云之间的镜像型对应关联性为核心，具体过程为：首先建立源点云到目标点云的前向对应关系，以捕获位于重叠区域的特征点；然后建立重叠区域的后向对应关系，以获取可靠匹配对集合；最后根据可靠匹配对估计最优刚体变换矩阵。此外，通过KD树构建和特征扩展两方面进行优化，以提升算法效率。所提算法仅依赖重叠区域匹配对集合，具有良好的鲁棒性和抗干扰能力。在斯坦福数据集上的实验结果表明：对于较低重叠度的数据集，所提算法在精度和效率上均优于以往的多数算法；对于较高重叠度的数据集，所提算法使精度平均提升28.8%

使效率平均提升47.9%。实验证明所提算法能快速且可靠地配准缺失点云。

Abstract

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references

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