Abstract
Prediction of interior room layout from observations on the exterior boundaries of a unit is sometimes needed in cases of emergencies when unit entry is denied. Seeing that 3D laser scanners are becoming smaller, lighter, and easier to carry around, this paper attempts to offer a fast method that can automatically reconstruct a room model relying merely on the 3D point cloud of the unit boundaries. The method first partitions the building floor space to generate the so-called “room seeds” from the intersections of lines that are extended from the detected wall segments. Then, the grammar approach compares different possible room configurations through a trial-and-error process to find the most possible one. The proposed method is tested on a real residential building case for validation. The proposed method may be useful in emergent cases when exact floor plans are not available. The method can be extended to other Manhattan-type buildings as long as the grammar rules are settled.
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