No abstract

Traditional documentation capabilities of laser scanning technology can be further exploited for urban modelling through the transformation of resulting point clouds into solid models compatible for computational analysis. This paper introduces such a technique through the combination of an angle criterion and voxelization. As part of that, a k-nearest neighbor (kNN) searching algorithm is implemented using a predefined number of kNN points combined with a maximum radius of the neighborhood, something not previously implemented. From this sample points are categorized as boundary or interior points. Façade features are determined based on underlying vertical and horizontal grid voxels of the feature boundaries by a grid clustering technique. The complete building model involving all full voxels is generated by employing the Flying Voxel method in order to relabel voxels inside openings or outside the facade as empty voxels. Experimental results on 3 different buildings, using 4 distinct sampling densities show successful detection of all openings, reconstruction of all building façades, and automatic filling of all improper holes. The maximum nodal displacement divergence was 1.6% compared to manually generated meshes from measured drawings. This fully automated approach rivals processing times of other techniques with the distinct advantage of extracting more boundary points, especially in less dense data sets (< 175pts/m 2 ), which may enable its more rapid exploitation of aerial laser scanning data and ultimately preclude needing a priori knowledge.

This paper presents the fundamental mathematics to determine the minimum crack width detectable with a terrestrial laser scanner in unit-based masonry. Orthogonal offset, interval scan angle, crack orientation, and crack depth are the main parameters. The theoretical work is benchmarked against laboratory tests using 4 samples with predesigned crack widths of 1-7mm scanned at orthogonal distances of 5.0-12.5m and at angles of 0˚-30˚. Results showed that absolute errors of crack width were mostly less than 1.37mm when the orthogonal distance varied 5.0-7.5m but significantly increased for greater distances. Orthogonal distance had a disproportionately negative effect compared to the scan angle.2

No abstract

ABSTRACT:In an effort to reconstruct geometric models of building façades from terrestrial laser scanning data directly without either manual intervention or any third party computer-aid design package, a new algorithm is introduced. The algorithm detects building boundaries and features and converts the point cloud data into a solid model appropriate for computational modeling. The algorithm combines a voxel-based technique with a Delaunay triangulation based criterion. In the first phase, the algorithm detects façade boundary points from raw data. The algorithm's second phase creates a solid model using voxels in a quadtree representation.Finally, the algorithm determines whether holes are actual openings or data deficits caused by occlusions and then fills unrealistic openings. The algorithm was applied to the façades of three masonry buildings. For these buildings, the algorithm successfully detected all openings and reconstructs the façade details correctly. Geometric validation of the models against measured drawings showed overall dimensions correct to 1.2%, mostly opening areas to 3%, and simulation results within 5% of those predicted by a CAD-based model.