应用激光2024，Vol.44Issue(1) ：144-154.DOI:10.14128/j.cnki.al.20244401.144

点云特征保留的精简方法研究

Research on Simplification Method of Point Cloud Feature Preservation

刘洋 高磊 吴学群 田赢
应用激光2024，Vol.44Issue(1) ：144-154.DOI:10.14128/j.cnki.al.20244401.144
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  • NSTL
  • 万方数据

点云特征保留的精简方法研究

Research on Simplification Method of Point Cloud Feature Preservation

刘洋 1高磊 2吴学群 1田赢1
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作者信息

  • 1. 昆明理工大学国土资源工程学院,云南昆明 600093
  • 2. 云南省投资控股集团有限公司,云南昆明 650000
  • 折叠

摘要

针对传统点云精简算法在精简点云时特征丢失严重、空洞较多等问题,提出一种顾及点云特征和完整性的点云精简算法.该算法首先利用点云的邻域法向夹角提取出模型的整体特征点;其次利用模糊C-均值聚类算法并依据点云曲率和快速点特征直方图提取出局部特征点;再次对非局部特征点则利用改进的体素精简法进行下采样得到非特征点;最后将各步所得点云进行融合,进而得到最终精简的点云.将所提算法与传统的方法和其他文献中的方法进行对比,并用描述数据集之间误差的定量指标Hausdorff距离作为精简精度的评价指标.经试验证明,对于Bunny数据集和Skull数据集,所提算法的Haus-dorff距离分别比随机精简法低约25％和39％,比曲率精简法低约86％和95％,比其他文献中的方法低约86％和81％.由此可见,所提精简算法具有较高的精简精度.

Abstract

Aiming at the problems of serious feature loss and more holes in the traditional point cloud simplification algorithm,a point cloud simplification algorithm considering the features and integrity of point clouds was proposed.Firstly,the whole feature points of the model are extracted by using the neighborhood normal Angle of the point cloud.Then the fuzzy C-means clustering algorithm is used to extract the local feature points according to the curvature of the point cloud and the fast point feature histogram.Then the non-local feature points are subsampled using the improved voxel reduction method to obtain the non-feature points.Finally,the point clouds obtained from each step are fused to obtain the final reduced point cloud.The pro-posed algorithm is compared with the traditional methods and method of other literature,and the Hausdorff distance,a quanti-tative index describing the error between datasets,is used as the evaluation index of the simplification accuracy.The experi-mental results show that the Hausdorff distance of the proposed algorithm on Bunny dataset and Skull dataset is about 25％and 39％lower than that of the random reduction method,about 86％and 95％lower than that of the curvature reduction method,and about 86％and 81％lower than method of other literature.It can be seen that the simplification algorithm in this paper has high simplification accuracy.

关键词

点云精简/邻域法向夹角/快速点特征直方图/模糊C-均值聚类算法/点云曲率/Hausdorff距离

Key words

point cloud simplification/normal angle of neighborhood/fast point feature histogram/fuzzy C-means cluste-ring algorithm/point cloud curvature/Hausdorff distance

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基金项目

国家自然科学基金地区基金项目(41961053)

国家自然科学基金地区基金项目(41961039)

出版年

2024
应用激光
上海市激光技术研究所

应用激光

CSTPCD北大核心
影响因子：0.461
ISSN：1000-372X
参考文献量23
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