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Metrics and methods for evaluating model-driven reality capture plans
Computer-Aided Civil and Infrastructure Engineering ( IF 9.6 ) Pub Date : 2021-05-07 , DOI: 10.1111/mice.12693
Amir Ibrahim 1 , Mani Golparvar‐Fard 2 , Khaled El‐Rayes 1
Affiliation  

This paper presents new metrics and methods for evaluating the quality of reality capture plans—commonly used to operate camera-mounted unmanned aerial vehicles (UAVs) or ground rovers—for construction progress monitoring and inspection of as-is conditions. Using 4D building information model (BIM) or 3D reality model as a priori, these metrics provide feedback on the quality of a plan (within a few minutes), accounting for resolution, visibility, accuracy, completeness of the capture, and satisfying battery capacity and line-of-sight requirements. A cloud-based system is introduced to create and optimize UAV/rover missions in the context of prior model. Results from real-world construction data sets demonstrate that the proposed metrics offer actionable insights into the accuracy and completeness of reality capture plans. Additionally, a capture plan—with a combination of canonical and noncanonical camera views—that satisfies the introduced metrics is statistically correlated with the quality of reconstructed reality. These metrics can improve computer-vision progress monitoring and inspection methods that rely on the construction site's appearance and geometry.

中文翻译:

评估模型驱动的现实捕捉计划的指标和方法

本文提出了评估现实捕捉计划质量的新指标和方法——通常用于操作安装在摄像头上的无人机 (UAV) 或地面漫游车——用于施工进度监测和现状检查。使用 4D 建筑信息模型 (BIM) 或 3D 现实模型作为先验,这些指标提供有关计划质量的反馈(几分钟内),考虑分辨率、可见性、准确性、捕获的完整性以及满足电池容量和视线要求。引入了基于云的系统,以在先前的背景下创建和优化无人机/漫游车任务。模型。来自真实世界建筑数据集的结果表明,提议的指标提供了对现实捕捉计划的准确性和完整性的可操作见解。此外,满足引入指标的捕获计划(结合规范和非规范摄像机视图)与重建现实的质量在统计上相关。这些指标可以改进依赖于施工现场外观和几何形状的计算机视觉进度监控和检查方法。
更新日期:2021-05-07
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