基于无人地面车辆补充采集的三维重构模型优化  

Supplementary capture using unmanned ground vehicle for 3D reconstruction model improvement

作　　者：杨东辉[1] 王昱昊 YANG Donghui;WANG Yuhao(School of Vehicle and Mobility,Tsinghua University,Beijing 100084,China)

机构地区：[1]清华大学车辆与运载学院,北京100084

出　　处：《汽车安全与节能学报》2024年第5期650-659,共10页Journal of Automotive Safety and Energy

基　　金：交通载运装备数字化与孪生系统项目(2023YFB4301800)。

摘　　要：为解决无人机单独采集图像生成三维(3D)重构模型存在破损和孔洞的问题,提出了一种基于无人地面车辆补充采集的3D模型优化方法。该方法耦合基于模型分辨率、三角网格结构和人工选点3种方法提取待优化区域,生成3D包围框和法向量信息,并利用3D重构质量启发式方法生成补充采集视点。结果表明:在该方法优化下,粗糙3D模型的低质量区域得到了显著改善,模型投影像素尺寸平均减少66%;该方法可以有效提升了3D模型重构质量,为室外大规模精细3D重构领域提供了可靠的解决方案。A 3D model improving method based on supplementary capture by unmanned ground vehicle was proposed to address the issue of damage and holes in 3D reconstruction models generated from images captured solely by unmanned ground vehicle.This method combined model resolution,triangular mesh structure,and manual point selection to extract areas needing improvement,generated 3D bounding boxes and normal vector information,and utilized heuristic methods to generate supplementary viewpoints.The results show that,under this method's optimization,the low-quality areas of the rough 3D model are significantly improved,with an average reduction of 66%in model projection pixel size.Therefore,this method effectively enhances the quality of 3D model reconstruction,providing a reliable solution for large-scale,detailed outdoor 3D reconstruction.

关 键 词：三维(3D)重构 模型优化 几何代理 视点规划 无人地面车辆 

分 类 号：TP23[自动化与计算机技术—检测技术与自动化装置]