一种基于平面特征的点云质量优化方法  

A method for optimizing point cloud quality based on plane features

作　　者：赵春晨 王宁[1,2] 杨谦 李捷斌[1,2] Zhao Chunchen;Wang Ning;Yang Qian;Li Jiebin(Shaanxi Polytechnic Institute,Xianyang 712000,China;Xianyang Key Laboratory of Digital City and Geospatial Big Data Technology,Xianyang 712000,China)

机构地区：[1]陕西工业职业技术学院,陕西咸阳712000 [2]咸阳市数字城市与地理空间大数据技术重点实验室,陕西咸阳712000

出　　处：《工程勘察》2024年第10期66-70,76,共6页Geotechnical Investigation & Surveying

基　　金：陕西工业职业技术学院青年科技创新团队(KCTD2022-01);陕西省教育厅2020年度一般专项科学研究计划(20JK0501)关中中心城市滑坡隐患区三维模拟分析及评估防护研究.

摘　　要：倾斜摄影测量技术目前被广泛应用于大规模城市级三维实景建模中,但对于建筑物的精细建模,倾斜摄影测量的测量精度还不能满足要求,密集重建生成的密集点云数据质量还需进一步提升。大部分城市建筑为规则建筑,本文提出一种基于平面特征的点云质量优化方法,用于提升采用倾斜摄影测量密集重建点云的数据质量,并与地面三维激光点云据进行对比。结果表明,该方法可以优化提升密集重建点云的数据质量。Oblique photogrammetry technology is currently widely used in large-scale level urban 3D real scene modeling.However,for precise modeling of buildings,the measurement accuracy of oblique photogrammetry cannot meet the requirements,and the quality of dense reconstruction point clouds needs to be further improved.Most urban buildings are regular buildings.This article proposes a point cloud quality optimization method based on planar features to improve the data quality of dense reconstructed point clouds using oblique photogrammetry.The comparison with ground 3D laser point clouds shows that this method can optimize and improve the data quality of dense reconstructed point clouds.

关 键 词：倾斜摄影测量 数据质量优化 密集重建点云 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]