顾及局部特征的三维点云建筑物轮廓精确化提取

doi:10.13474/j.cnki.11-2246.2023.0231

测绘通报 ›› 2023, Vol. 0 ›› Issue (8): 51-56.doi: 10.13474/j.cnki.11-2246.2023.0231

顾及局部特征的三维点云建筑物轮廓精确化提取

徐锦芳¹, 罗小龙¹, 蒋卫东³, 钟康¹, 冉星星^1,2, 李冰洋^1,2

1. 长江大学地球科学学院, 湖北武汉 430100;
2. 自然资源部城市国土资源监测与仿真重点实验室, 广东深圳 518000;
3. 西南科技大学计算机科学与技术学院, 四川绵阳 621010

收稿日期:2022-10-26 发布日期:2023-09-01
通讯作者: 罗小龙。E-mail:lxl2001181@163.com
作者简介:徐锦芳(1998-),女,硕士生,研究方向为三维点云数据处理与应用。E-mail:xjfxjf0405@gmail.com
基金资助:
自然资源部城市国土资源监测与仿真重点实验室开放基金(KF-2021-06-093)

Extracting accurate building outlines from 3D point clouds considering local features

XU Jinfang¹, LUO Xiaolong¹, JIANG Weidong³, ZHONG Kang¹, RAN Xingxing^1,2, LI Bingyang^1,2

1. School of Geosciences, Yangtze University, Wuhan 430100, China;
2. The Project Supported by the Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen 518000, China;
3. School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang 621010, China

Received:2022-10-26 Published:2023-09-01

摘要/Abstract

摘要： 建筑物是城市的重要组成部分,从三维点云数据中精细化地提取建筑物特征是当前研究的热点。本文提出了一种顾及局部特征的三维点云建筑物轮廓精确化提取方法。首先,采用基于统计学的滤波预处理方法,分离地面点与非地面点,去除离群点,降低点云数量;然后,通过基于改进3D Hough变换的建筑物立面提取方法,提取点云数据的多立面,提高立面提取的精度和效率;最后,采用基于降维边界索引的点云轮廓精准提取方法,获取局部特征和外部轮廓特征。结果表明,该方法能够充分兼顾建筑物的整体外部轮廓及局部细节特征,高效准确地实现建筑物的精确化提取,为城市规划、城市更新等相关应用提供技术支持。

关键词: 局部特征, 改进3D Hough变换算法, α-shape算法, 精细化

Abstract: Buildings are an important component of cities, and extracting building features from 3D point clouds data in a refined manner is currently a research hotspot. The paper proposes a methods for accurately extracting building outlines from 3D point clouds that considers local features. Firstly, a statistical-based filtering pre-processing method is used to separate ground points and non-ground points, remove outliers, and reduce the number of point clouds. Secondly, a building facade extraction method based on an improved 3D Hough transform is used to extract multiple facades of the point cloud data to improve the accuracy and efficiency of facade extraction. Finally, a point cloud outlines extraction method based on dimensionality reduction boundary indexing to obtain both local features and external outline features. The results demonstrate that our methods can effectively and accurately extract building outlines by fully considering both the overall external contours and local detailed features of the buildings. This methods provides technical support for various applications, such as urban planning and urban renewal.

Key words: local features, improved 3D Hough transformation algorithm, α-shape algorithm, refinement

中图分类号:

P237

徐锦芳, 罗小龙, 蒋卫东, 钟康, 冉星星, 李冰洋. 顾及局部特征的三维点云建筑物轮廓精确化提取[J]. 测绘通报, 2023, 0(8): 51-56.

XU Jinfang, LUO Xiaolong, JIANG Weidong, ZHONG Kang, RAN Xingxing, LI Bingyang. Extracting accurate building outlines from 3D point clouds considering local features[J]. Bulletin of Surveying and Mapping, 2023, 0(8): 51-56.

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顾及局部特征的三维点云建筑物轮廓精确化提取

Extracting accurate building outlines from 3D point clouds considering local features

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