Automatic construction progress documentation and metric evaluation of execution work in confined building interiors requires particularly reliable geometric evaluation and interpretation of statistically uncertain as-built point clouds. This paper presents a method for high-resolution change detection based on dense 3D point clouds from terrestrial laser scanning (TLS) and the discretization of space by voxels. In order to evaluate the metric accuracy of a BIM according to the Level of Accuracy (LOA) specification, the effects of laser range measurements on the occupancy of space are modeled with belief functions and evaluated using Dempster and Shafer's theory of evidence. The application is demonstrated on the point cloud data of multi temporal scanning campaigns of real indoor reconstructions. The results show that TLS point clouds are suitable to verify a given BIM up to LOA 40 if special attention is paid to the scanning geometry during the acquisition. The proposed method can be used to document construction progress, verify and even update the LOA status of a given BIM, confirming valid and BIM-compliant as-built models for further planning.

自动施工进度文档和对受限建筑内部执行工作的度量评估需要特别可靠的几何评估和统计上不确定的竣工点云的解释。本文提出了一种基于来自地面激光扫描 (TLS) 的密集 3D 点云和体素空间离散化的高分辨率变化检测方法。为了根据精度等级 (LOA) 规范评估 BIM 的度量精度，激光距离测量对空间占用的影响使用置信函数建模，并使用 Dempster 和 Shafer 的证据理论进行评估。该应用程序在真实室内重建的多时间扫描活动的点云数据上进行了演示。结果表明，如果在采集过程中特别注意扫描几何形状，则 TLS 点云适用于验证最高 LOA 40 的给定 BIM。所提出的方法可用于记录施工进度、验证甚至更新给定 BIM 的 LOA 状态，确认有效且符合 BIM 的竣工模型以进行进一步规划。