3D Simulation Landscape Design Based on Image Sensor

J. Sensors Pub Date : 2022-08-18 DOI:10.1155/2022/1577945
Yao Lu, Bingyan Chen, Yan Xing, Yang Geon Seok
{"title":"3D Simulation Landscape Design Based on Image Sensor","authors":"Yao Lu, Bingyan Chen, Yan Xing, Yang Geon Seok","doi":"10.1155/2022/1577945","DOIUrl":null,"url":null,"abstract":"In order to solve the problem of heavy workload of landscape plant modeling, the lack of efficient auxiliary or automatic methods for establishing three-dimensional models for various landscape plants, and the general three-dimensional models of landscape plants which cannot reflect the natural growth of plants and the interaction between the environment, this paper proposes a method of three-dimensional simulation of landscape design based on image sensors. This method includes the construction of three-dimensional image simulation landscape feature analysis function and rationality judgment model, so as to provide theoretical support for landscape design. The experimental results show that the matching number and matching rate of landscape feature points obtained by the traditional deep evaluation method are lower than those obtained by the 3D image simulation method used in this paper, and the steps of image feature points matching are relatively simple. With the gradual expansion of the scope, the accuracy of the three-dimensional image simulation judgment method used in this paper is gradually improved, up to 89%, while the traditional method is always maintained at about 40%. Conclusion. The 3D simulation landscape design method based on image sensor has higher accuracy and wider application prospect.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"1 1","pages":"1-7"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Sensors","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2022/1577945","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

In order to solve the problem of heavy workload of landscape plant modeling, the lack of efficient auxiliary or automatic methods for establishing three-dimensional models for various landscape plants, and the general three-dimensional models of landscape plants which cannot reflect the natural growth of plants and the interaction between the environment, this paper proposes a method of three-dimensional simulation of landscape design based on image sensors. This method includes the construction of three-dimensional image simulation landscape feature analysis function and rationality judgment model, so as to provide theoretical support for landscape design. The experimental results show that the matching number and matching rate of landscape feature points obtained by the traditional deep evaluation method are lower than those obtained by the 3D image simulation method used in this paper, and the steps of image feature points matching are relatively simple. With the gradual expansion of the scope, the accuracy of the three-dimensional image simulation judgment method used in this paper is gradually improved, up to 89%, while the traditional method is always maintained at about 40%. Conclusion. The 3D simulation landscape design method based on image sensor has higher accuracy and wider application prospect.
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
基于图像传感器的三维仿真景观设计
为了解决景观植物建模工作量大,各种景观植物缺乏高效的辅助或自动建立三维模型的方法,以及一般的景观植物三维模型不能反映植物的自然生长和与环境的相互作用等问题,本文提出了一种基于图像传感器的景观设计三维模拟方法。该方法包括构建三维图像模拟景观特征分析功能和合理性判断模型,从而为景观设计提供理论支持。实验结果表明,传统深度评价方法获得的景观特征点匹配数量和匹配率低于本文所采用的三维图像模拟方法,且图像特征点匹配步骤相对简单。随着范围的逐渐扩大,本文所采用的三维图像仿真判断方法的精度逐渐提高,达到89%,而传统方法始终保持在40%左右。结论。基于图像传感器的三维仿真景观设计方法具有更高的精度和更广阔的应用前景。
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
Index Construction and Application of School-Enterprise Collaborative Education Platform Based on AHP Fuzzy Method in Double Creation Education Practice Optimization of Intelligent Display Mode of Museum Cultural Relics Based on Intelligent Wireless Sensor Network Feature Extraction Method of Art Visual Communication Image Based on 5G Intelligent Sensor Network Scene Classification Using Deep Networks Combined with Visual Attention Spatial Expression of Multifaceted Soft Decoration Elements: Application of 3D Reconstruction Algorithm in Soft Decoration and Furnishing Design of Office Space
×
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