Automated Indoor Image Localization to Support a Post-Event Building Assessment
Automated Indoor Image Localization to Support a Post-Event Building Assessment
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DOI：
10.3390/s20061610
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发表时间：
2020-03
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通讯作者：
Xiaoyu Liu;S. Dyke;C. Yeum;Ilias Bilionis;A. Lenjani;Jongseong Choi
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文献类型：
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作者：
Xiaoyu Liu;S. Dyke;C. Yeum;Ilias Bilionis;A. Lenjani;Jongseong Choi
图像数据仍然是事后建筑评估和记录的重要工具。每次自然灾害发生后，工程师团队都会做出重大努力，访问受影响地区并收集有用的图像数据。一般来说，全球定位系统（GPS）可提供用于定位图像数据的有用空间信息。然而，当在GPS信号弱或中断的地方（诸如建筑物的室内空间）捕获图像时，收集这样的信息是具有挑战性的。无法记录图像的位置阻碍了对这些图像的分析、组织和记录，因为它们缺乏足够的空间背景。在这项工作中，我们开发了一种方法来本地化图像，并将它们链接到结构图上的位置。使用紧凑型摄像机可以很容易地沿着穿过建筑物的路径沿着收集图像流。这些图像可以用于计算每个图像在3D点云模型中的相对位置，该3D点云模型是使用视觉测距算法重建的。图像还可以用于使用运动恢复结构算法来创建感兴趣的建筑物组件的局部3D纹理模型。使用时间信息将为建筑物评估收集的一组并行图像链接到图像流。通过将点云模型投影到结构图上，图像可以覆盖到图形上，提供使用这些图像所需的清晰上下文信息。此外，在这些图像中捕获的组件或感兴趣的损坏可以在3D中重建，从而实现具有足够地理空间背景的详细评估。该技术是通过模拟事件后的建筑评估和数据收集在一个真实的建筑。
Image data remains an important tool for post-event building assessment and documentation. After each natural hazard event, significant efforts are made by teams of engineers to visit the affected regions and collect useful image data. In general, a global positioning system (GPS) can provide useful spatial information for localizing image data. However, it is challenging to collect such information when images are captured in places where GPS signals are weak or interrupted, such as the indoor spaces of buildings. The inability to document the images’ locations hinders the analysis, organization, and documentation of these images as they lack sufficient spatial context. In this work, we develop a methodology to localize images and link them to locations on a structural drawing. A stream of images can readily be gathered along the path taken through a building using a compact camera. These images may be used to compute a relative location of each image in a 3D point cloud model, which is reconstructed using a visual odometry algorithm. The images may also be used to create local 3D textured models for building-components-of-interest using a structure-from-motion algorithm. A parallel set of images that are collected for building assessment is linked to the image stream using time information. By projecting the point cloud model to the structural drawing, the images can be overlaid onto the drawing, providing clear context information necessary to make use of those images. Additionally, components- or damage-of-interest captured in these images can be reconstructed in 3D, enabling detailed assessments having sufficient geospatial context. The technique is demonstrated by emulating post-event building assessment and data collection in a real building.