节点优化与贴图重构的实景三维Mesh模型轻量化方法  

A lightweighting method to realistic 3D Mesh models using node optimization and mapping UV reconstruction

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作  者:张永庭 姚岐 沈晓帆 梅靖 高铁 ZHANG Yongting;YAO Qi;SHEN Xiaofan;MEI Jing;GAO Tie(Surveying,Mapping and Geographic Information Institute of the Ningxia Hui Autonomous Region,Yinchuan 751100,China;Chengdu Wanjin Technology Co.,Ltd.,Chengdu 610000,China)

机构地区:[1]宁夏回族自治区测绘地理信息院,银川750000 [2]成都万锦科技有限公司,成都610000

出  处:《测绘科学》2024年第12期94-103,共10页Science of Surveying and Mapping

摘  要:为解决实景三维Mesh模型数据量大、渲染速度慢等问题,需要对实景三维Mesh模型进行轻量化处理,该文在现有轻量化方法的基础上,提出了一种新的实景三维Mesh模型轻量化方法,加入了模型节点优化和贴图UV重构。通过选择实验区对现有方法和本文方法进行实验对比,结果表明,现有算法通过对原始数据进行顶点优化、几何简化等压缩方式,整体数据量减少47.5%。本文算法通过进行节点合并和贴图UV重构,减少了模型数量,且在不影响纹理精度的前提下,提升了模型整体贴图使用率,降低了模型贴图尺寸,模型数据量减少64.5%。在1∶50000比例尺下,对比原始数据大幅提升了渲染效率。在1∶1500比例尺下,本文算法处理模型数据对比现有算法,渲染时间减少61.5%。To address problems such as large data volume and slow rendering speed in large-area real-area three-dimensional(3D)Mesh models,in this paper,based on the existing lightweighting methods,we propose a new lightweighting method for real 3D Mesh models,which incorporates model node optimization and texture UV reconstruction.By selecting the experimental area to experimentally compare the existing method and this paper's method,the results show that the existing algorithm reduces the overall data volume by 47.5%by performing vertex optimization,geometric simplification and other compression methods on the original data.This paper's algorithm reduces the number of models by performing node merging and mapping UV reconstruction,and without affecting the texture accuracy,it improves the overall texture utilization rate of the model,reduces the texture size of the model,and reduces the model data volume by 64.5%.At 1∶50000 scale,the rendering efficiency is greatly improved compared to the original data.At 1∶1500 scale,the algorithm in this paper processes the model data comparing with the existing algorithm,the rendering time is reduced by 61.5%.

关 键 词:实景三维Mesh模型 轻量化 节点优化 贴图UV重构 

分 类 号:P237[天文地球—摄影测量与遥感]

 

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