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基于多平面分割和矩阵变换的航摄边坡点云滤波算法

余加勇 杨宇驰 王昱东 周翠竹

湖南大学学报(自然科学版)2024,Vol.51Issue(11):12-22,11.
湖南大学学报(自然科学版)2024,Vol.51Issue(11):12-22,11.DOI:10.16339/j.cnki.hdxbzkb.2024103

基于多平面分割和矩阵变换的航摄边坡点云滤波算法

An Aerial Photography Slope Point Cloud Filtering Algorithm Based on Multi-Plane Segmentation and Matrix Transformations

余加勇 1杨宇驰 1王昱东 1周翠竹1

作者信息

  • 1. 湖南大学 土木工程学院,湖南 长沙 410082
  • 折叠

摘要

Abstract

Point cloud filtering is a crucial processing technique for separating ground points from non-ground points and obtaining the most accurate ground point cloud.It serves as the foundation for landslide identification in highway slope point clouds.To address issues such as slow processing speed,low result accuracy,and high error rates encountered by traditional point cloud filtering algorithms in slope scenarios,an airborne slope point cloud filtering algorithm based on multi-plane segmentation and matrix transformation is proposed.This method initially employs a region growing algorithm based on curvature for multi-plane segmentation of the slopes,resulting in multiple sub-point clouds of the slopes.Subsequently,it fits plane models for these sub-point clouds and uses rotation matrices to spatially transform them onto a horizontal plane.Non-ground points are separated by simulating fabric settling with a distance threshold.Finally,the inverse of the rotation matrix is applied for spatial position restoration,yielding the filtered slope point cloud.High-precision point cloud models are obtained using a fine approximation flight route design method for algorithm testing in various slope scenarios.Results are compared with those of other traditional filtering algorithms,demonstrating that the algorithm in this paper outperforms the others with total errors of 7.11%,4.15%,1.45%,and 4.41%in all experiments,respectively.Furthermore,the Kappa coefficient values are 0.77,0.90,0.96,and 0.90,all of which are the highest among all tested algorithms.The proposed algorithm exhibits high accuracy and applicability,particularly in complex slope scenarios characterized by varying terrains and vegetation cover.It offers a new solution for point cloud filtering in highway slope applications.

关键词

公路边坡/无人机/航摄点云/点云滤波/多平面分割/矩阵变换

Key words

road slopes/unmanned aerial vehicle/aerial photogrammetric point clouds/point cloud filtering/multi-plane segmentation/matrix transformations

分类

建筑与水利

引用本文复制引用

余加勇,杨宇驰,王昱东,周翠竹..基于多平面分割和矩阵变换的航摄边坡点云滤波算法[J].湖南大学学报(自然科学版),2024,51(11):12-22,11.

基金项目

湖南省水利科技项目(XSKJ2021000-46),Hunan Water Resources Science and Technology Project(XSKJ2021000-46) (XSKJ2021000-46)

江苏省水利科技项目(2021074),Jiangsu Water Resources Science and Technology Project(2021074) (2021074)

湖南大学学报(自然科学版)

OA北大核心CSTPCD

1674-2974

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