Research on Key Technologies of 3D Real Scene Visualization Based on Multi-source Observation Data Fusion

Qiang Jing, Hongzhi Miao, Xiaowei Yang, Huifang Ming, Hui Yin
{"title":"Research on Key Technologies of 3D Real Scene Visualization Based on Multi-source Observation Data Fusion","authors":"Qiang Jing, Hongzhi Miao, Xiaowei Yang, Huifang Ming, Hui Yin","doi":"10.1109/ICGMRS55602.2022.9849224","DOIUrl":null,"url":null,"abstract":"Based on the big data of multi-source observation of the underwater environment of the Hong Kong-Zhuhai-Macao Bridge,this study constructed an underwater three-dimensional(3D) scene with multi-source data fusion,realized the visual presentation and management of the underwater environment of large structures,and satisfied the requirements of visual operation and safety detection and protection of large structures.In this paper,the key technologies related to multisource spatio-temporal big data fusion and 3D real scene visualization were studied,a multi-storage distributed storage framework for hybrid spatio-temporal big data is constructed,a hierarchical organization model for spatio-temporal big data is proposed,and multi-source observation data fusion of large underwater structures is realized.Furthermore,3D scenes are rendered based on technologies such as WebGL,onshore/undersea terrain simulation,and gridding to realize 3D real-world visualization.The construction of a 3D real scene visualization model based on multi-source spatiotemporal big data fusion can quickly realize the deformation monitoring and spatiotemporal deduction of the Hong Kong-Zhuhai-Macao Bridge.Based on the fused 3D scene,the evolution analysis of underwater terrain and stratum can be conducted,which can effectively support the monitoring and management of the underwater environment of large structures.","PeriodicalId":129909,"journal":{"name":"2022 3rd International Conference on Geology, Mapping and Remote Sensing (ICGMRS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 3rd International Conference on Geology, Mapping and Remote Sensing (ICGMRS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICGMRS55602.2022.9849224","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Based on the big data of multi-source observation of the underwater environment of the Hong Kong-Zhuhai-Macao Bridge,this study constructed an underwater three-dimensional(3D) scene with multi-source data fusion,realized the visual presentation and management of the underwater environment of large structures,and satisfied the requirements of visual operation and safety detection and protection of large structures.In this paper,the key technologies related to multisource spatio-temporal big data fusion and 3D real scene visualization were studied,a multi-storage distributed storage framework for hybrid spatio-temporal big data is constructed,a hierarchical organization model for spatio-temporal big data is proposed,and multi-source observation data fusion of large underwater structures is realized.Furthermore,3D scenes are rendered based on technologies such as WebGL,onshore/undersea terrain simulation,and gridding to realize 3D real-world visualization.The construction of a 3D real scene visualization model based on multi-source spatiotemporal big data fusion can quickly realize the deformation monitoring and spatiotemporal deduction of the Hong Kong-Zhuhai-Macao Bridge.Based on the fused 3D scene,the evolution analysis of underwater terrain and stratum can be conducted,which can effectively support the monitoring and management of the underwater environment of large structures.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于多源观测数据融合的三维真实场景可视化关键技术研究
本研究以港珠澳大桥水下环境多源观测大数据为基础,构建了多源数据融合的水下三维场景,实现了大型构筑物水下环境的可视化呈现与管理,满足了大型构筑物可视化操作和安全检测防护的要求。本文研究了多源时空大数据融合与三维真实场景可视化相关关键技术,构建了混合时空大数据多存储分布式存储框架,提出了时空大数据分层组织模型,实现了大型水下结构物多源观测数据融合。基于WebGL、陆上/海底地形模拟、网格化等技术渲染三维场景,实现三维真实世界可视化。构建基于多源时空大数据融合的三维实景可视化模型,可快速实现港珠澳大桥的变形监测和时空演绎。基于融合的三维场景,可以进行水下地形和地层的演化分析,可以有效地支持大型构筑物水下环境的监测和管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Research on UAV remote sensing multispectral image compression based on CNN MDNet: A Multi-modal Dual Branch Road Extraction Network Using Infrared Information Quantitative Evaluation of Digital Orthophoto Map Influence of shallow ocean front on propagation characteristics of low frequency sound energy flow Application of GA-BP neural network in prediction of chl-a concentration in Wuliangsu Lake
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1