Intelligent City 3D Modeling Model Based on Multisource Data Point Cloud Algorithm

Author:

Wu Youping1ORCID,Zhou Zhihui1ORCID

Affiliation:

1. Department of Applied Engineering, Gandong College, Fuzhou, Jiangxi 344000, China

Abstract

With the rapid development of smart cities, intelligent navigation, and autonomous driving, how to quickly obtain 3D spatial information of urban buildings and build a high-precision 3D fine model has become a key problem to be solved. As the two-dimensional mapping results have constrained various needs in people’s social life, coupled with the concept of digital city and advocacy, making three-dimensional, virtualization and actualization become the common pursuit of people’s goals. However, the original point cloud obtained is always incomplete due to reasons such as occlusion during acquisition and data density decreasing with distance, resulting in extracted boundaries that are often incomplete as well. In this paper, based on the study of current mainstream 3D model data organization methods, geographic grids and map service specifications, and other related technologies, an intelligent urban 3D modeling model based on multisource data point cloud algorithm is designed for the two problems of unified organization and expression of urban multisource 3D model data. A point cloud preprocessing process is also designed: point cloud noise reduction and downsampling to ensure the original point cloud geometry structure remain unchanged, while improving the point cloud quality and reducing the number of point clouds. By outputting to a common 3D format, the 3D model constructed in this paper can be applied to many fields such as urban planning and design, architectural landscape design, urban management, emergency disaster relief, environmental protection, and virtual tourism.

Funder

Science and Technology Research Project in Jiangxi Provincial Department of Education

Publisher

Hindawi Limited

Subject

Analysis

Reference10 articles.

1. Application of point cloud fusion algorithm of multi-source data in 3D modeling of smart city;H. Xiaobing;Beijing Surveying and Mapping,2021

2. 3D modeling method and accuracy analysis based on fusion of multi-source data;Z. Lihui;Beijing Surveying and Mapping,2020

3. Automatic Reconstruction of Multi-Level Indoor Spaces from Point Cloud and Trajectory[J];W. X. Dong;Sensors,2021

4. A Practical 3D Reconstruction Method for Weak Texture Scenes[J];Z. Longqi;Remote Sensing,2021

5. A method of reconstructing 3D model from 2D geological cross-section based on self-adaptive spatial sampling: A case study of Cretaceous McMurray reservoirs in a block of Canada;L. Yichen;Petroleum Exploration and Development,2021

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3