This paper presents an alternative to segmentation of point clouds tailored specifically to large-scale steel buildings. Typical segmentation approaches process the 3D point data directly and focus on large blocky structures such as concrete; these are not generalizable to smaller, more complex geometries found in steel elements. The method takes advantage of image processing techniques by utilizing 2D "slices" of the point cloud, rather than the original 3D point cloud. Centroids of targeted structural cross sections are extracted from these slices using 2D convolution as a template-matching operation, and then projected back to 3D. From this, member centroidal axes are extracted using a custom linear region growing algorithm to create a 1D beam line model, including connections. Experimental results from scans of four prefabricated steel buildings indicate that the method is robust to variations in framing systems, clutter (e.g., obstructions, nonstructural elements), and point cloud sparsity.
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