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Geo-registering UAV-captured close-range images to GIS-based spatial model for building facade inspections

机译:基于GIS的基于GIS的空间模型的地理登记无人机近距离图像

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There is a growing trend in the application of Unmanned Aerial Vehicle (UAV) systems for visual inspection of building facades. Current practices remain at a low efficiency to manage the large amount of UAV-collected close-range facade images to support the inspection and documentation of facade anomalies such as cracks and corrosions. This paper proposes a GIS-based two-step procedure to streamline the process of the management of UAV-collected images for supporting building facade inspection. First, a 2D GIS spatial model of building facades is created by net-unfolding facade surfaces around the building footprint in GIS to store the geometric and geographic information of building facades. Then, the UAV-collected images are automatically geo-registered to the 2D GIS spatial model through computer vision techniques applied in GIS. An experimental case study is also presented to demonstrate the process and evaluate the performance of the proposed method. It is demonstrated that the GIS-based spatial model of net-unfolded building facades allows for an efficient and effective registration of UAV-captured close-range facade images without apparent loss of pixel data. Provided with image data processing capabilities to detect and assess facade anomalies, the proposed GIS-based workflow can contribute to an automated documentation of UAV-based facade inspections to support the decision-making of further maintenance actions.
机译:无人驾驶飞行器(UAV)系统在视觉检查建筑立面的目视检查中存在日益增长的趋势。目前的实践仍然处于低效率,以管理大量的无人机收集的近距离立面图像,以支持视野异常(如裂缝和腐蚀)的检查和文件。本文提出了一种基于GIS的两步程序,用于简化用于支持建筑立面检查的无人机收集图像的管理过程。首先,建筑物外观的2D GIS空间模型由GIS中的建筑物占地面积周围的网展开门面创建,用于存储建筑物外墙的几何和地理信息。然后,通过在GIS中应用的计算机视觉技术将UAV收集的图像自动注册到2D GIS空间模型。还提出了实验案例研究以证明该过程并评估所提出的方法的性能。证明基于GIS的网络空间模型的网络展开建筑物外观允许无人机捕获的近距离立面图像的高效和有效的登记,而无需明显丢失像素数据。提供了用于检测和评估外观异常的图像数据处理功能,所提出的基于GIS的工作流程可以为基于UV的外观检查的自动化文档提供有助于支持进一步维护行动的决策。

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