Automatic Detection of Building Equipment using Laser Intensity of MLS Point Cloud

Building Information Modeling (BIM) is being increasingly used in the maintenance of buildings. Since 3D models do not exist for old buildings, it is common to create BIM from 3D scanned point clouds. To date, it has become possible to construct simple BIM consisting of major components such as floors, walls, ceilings, and columns almost automatically. However, automatic construction of detailed BIM including building equipment (lighting, air conditioning, fire alarm, etc.) necessary for building maintenance has not yet been achieved. These are often attached to ceilings and walls, and are difficult to recognize because of their small surface area and thickness. In this paper, we propose a method to detect building equipment using laser reflection intensity to automatically construct detailed BIM from point clouds of buildings by mobile laser scanners (MLS). In this method, first, the effects of distance and incident angle included in the reflection intensity are eliminated based on polynomial approximation, and the reflection intensity value of ceilings and walls made of the same material is approached to a constant value. Next, since the corrected intensity follows a normal distribution, a set of points that deviate from the normal distribution is extracted as building equipment candidates by thresholding. Finally, the point cloud is converted into an image representation, and each equipment is extracted using morphological and labeling process. Through various experiments targeting the ceilings and a wall of buildings, the proposed method achieved a high detection rate.