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Computer-Aided Approach for Rapid Post-Event Visual Evaluation of a Building Façade

机译:快速进行事后视觉评估建筑立面的计算机辅助方法

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摘要

After a disaster strikes an urban area, damage to the façades of a building may produce dangerous falling hazards that jeopardize pedestrians and vehicles. Thus, building façades must be rapidly inspected to prevent potential loss of life and property damage. Harnessing the capacity to use new vision sensors and associated sensing platforms, such as unmanned aerial vehicles (UAVs) would expedite this process and alleviate spatial and temporal limitations typically associated with human-based inspection in high-rise buildings. In this paper, we have developed an approach to perform rapid and accurate visual inspection of building façades using images collected from UAVs. An orthophoto corresponding to any reasonably flat region on the building (e.g., a façade or building side) is automatically constructed using a structure-from-motion (SfM) technique, followed by image stitching and blending. Based on the geometric relationship between the collected images and the constructed orthophoto, high-resolution region-of-interest are automatically extracted from the collected images, enabling efficient visual inspection. We successfully demonstrate the capabilities of the technique using an abandoned building of which a façade has damaged building components (e.g., window panes or external drainage pipes).
机译:灾难袭击市区后,建筑物外墙的损坏可能会产生危险的坠落危险,危害行人和车辆。因此,必须对建筑立面进行快速检查,以防止可能造成生命和财产损失。利用新的视觉传感器和相关的传感平台(例如无人机)的能力将加快这一过程,并减轻通常与高层建筑中基于人的检查相关的时空限制。在本文中,我们开发了一种使用从无人机收集的图像对建筑物立面进行快速,准确的视觉检查的方法。使用动感结构(SfM)技术自动构造与建筑物上任意合理平坦区域(例如,立面或建筑物侧面)相对应的正射影像,然后进行图像拼接和混合。根据收集的图像与所构造的正射影像之间的几何关系,可以从收集的图像中自动提取高分辨率的关注区域,从而实现高效的视觉检查。我们成功地使用了立面损坏了建筑物组件(例如窗玻璃或外部排水管)的废弃建筑物来证明了该技术的功能。

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