While Unmanned Aerial Vehicles (UAVs) are increasingly used for building façade inspections, their advantages have not been fully leveraged due to the challenge in gaining a fast and holistic understanding of as-is building conditions from fragmented images. This paper describes a framework to address the problem by registering UAV images into a Building Information Model (BIM) in three phases: (1) Extract position and optical parameters from UAV images to configure virtual cameras in BIM and generate template images; (2) Employ an improved generalised Hough transform (GHT) to extract building façade components with arbitrary shapes; (3) Project UAV images onto an orthophoto and incorporate them into 2D and 3D views. Finally, a Dynamo prototype is developed to automate the process. Computer simulations and field experiments confirmed a mean image-to-BIM registration error of within 21 mm, demonstrating the proposed approach has the potential to facilitate UAV-enabled building façade inspection.

虽然无人驾驶飞行器 (UAV) 越来越多地用于建筑外墙检查，但由于难以从碎片图像中快速、全面地了解建筑状况，因此它们的优势尚未得到充分利用。本文描述了一个通过将无人机图像注册到建筑信息模型 (BIM) 中来解决该问题的框架，分为三个阶段：(1) 从无人机图像中提取位置和光学参数，以在 BIM 中配置虚拟相机并生成模板图像；(2) 采用改进的广义霍夫变换(GHT)提取任意形状的建筑立面构件；(3) 将无人机图像投影到正射影像上，并将它们合并到 2D 和 3D 视图中。最后，开发了一个 Dynamo 原型来自动化该过程。