Concrete defect information is of vital importance to building maintenance. Increasingly, computer vision has been explored for automated concrete defect detection. However, existing studies suffer from the challenging issue of false positives. In addition, 3D reconstruction of the defects to pinpoint their positions and geometries has not been sufficiently explored. To address these limitations, this study proposes a novel computational approach for detecting and reconstructing concrete defects from geotagged aerial images. A bundle registration algorithm is devised to align a batch of aerial photographs with a building information model (BIM). The registration enables the retrieval of material semantics in BIM to determine the regions of interest for defect detection. It helps rectify the camera poses of the aerial images, enabling precise defect reconstruction. Experiments demonstrate the effectiveness of the approach, which significantly reduced the false discovery rate from 70.8% to 56.8%, resulting in an intersection over union 6.4% higher than that of the traditional method. The geometry of the defects was successfully reconstructed in 3D world space. This study opens a new avenue to advance the field of defect detection by exploiting the rich information from BIM. The approach can be deployed at scale, supporting urban renovation, numerical simulation, and other smart applications.

中文翻译：

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通过将航拍图像与语义丰富的建筑信息模型对齐来自动检测和重建混凝土缺陷

混凝土缺陷信息对于建筑物维护至关重要。计算机视觉已越来越多地被探索用于自动化混凝土缺陷检测。然而，现有研究存在误报这一具有挑战性的问题。此外，尚未充分探索缺陷的 3D 重建以查明其位置和几何形状。为了解决这些局限性，本研究提出了一种新的计算方法，用于从地理标记的航拍图像中检测和重建混凝土缺陷。设计了一种捆绑配准算法，将一批航拍照片与建筑信息模型 (BIM) 对齐。注册可以检索 BIM 中的材料语义，以确定缺陷检测的兴趣区域。它有助于纠正航拍图像的相机姿势，实现精确的缺陷重建。实验证明了该方法的有效性，该方法将错误发现率从 70.8% 显着降低到 56.8%，从而使 intersection over union 比传统方法高出 6.4%。在 3D 世界空间中成功重建了缺陷的几何形状。这项研究通过利用来自 BIM 的丰富信息，为推进缺陷检测领域开辟了一条新途径。该方法可以大规模部署，支持城市改造、数值模拟和其他智能应用。在 3D 世界空间中成功重建了缺陷的几何形状。这项研究通过利用来自 BIM 的丰富信息，为推进缺陷检测领域开辟了一条新途径。该方法可以大规模部署，支持城市改造、数值模拟和其他智能应用。在 3D 世界空间中成功重建了缺陷的几何形状。这项研究通过利用来自 BIM 的丰富信息，为推进缺陷检测领域开辟了一条新途径。该方法可以大规模部署，支持城市改造、数值模拟和其他智能应用。