Void-growing: a novel Scan-to-BIM method for manhattan world buildings from point cloud
Yuandong Pan, Alexander Braun, André Borrmann, Ioannis Brilakis
Abstract
The automated generation of 3D models of buildings from point clouds is under heavy research. Currently, this Scan-to-BIM process requires high manual effort, and the previous research in buildings under low occlusion level. We propose a novel “void-growing” approach that extracts walls, floors, and ceilings automatically. Different from the majority of current approaches starting with detecting surfaces of elements, our approach grows the void volume space inside a room first and it performs well in occluded environments. It can reconstruct simple cuboid rooms and complex rooms like L-shape and U-shape rooms. Different ceiling heights caused by suspended ceilings can also be represented.