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• W3109492753 startingPage "103503" @default.
• W3109492753 abstract "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 façade images to support the inspection and documentation of façade 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 façade inspection. First, a 2D GIS spatial model of building façades is created by net-unfolding façade surfaces around the building footprint in GIS to store the geometric and geographic information of building façades. 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 façades allows for an efficient and effective registration of UAV-captured close-range façade 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 façade inspections to support the decision-making of further maintenance actions." @default.
• W3109492753 created "2020-12-07" @default.
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• W3109492753 date "2021-02-01" @default.
• W3109492753 modified "2023-10-17" @default.
• W3109492753 title "Geo-registering UAV-captured close-range images to GIS-based spatial model for building façade inspections" @default.
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• W3109492753 doi "https://doi.org/10.1016/j.autcon.2020.103503" @default.
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