The as-built building information model (BIM) has a huge potential for enhancing the efficiency of building and
maintenance operations. To facilitate existing-structure data acquisition for the as-built BIM, a terrestrial laser
scanner, which is fast, simple to use, and yet highly accurate, is widely employed. However, as-built BIM creation
of building interiors using scanned point clouds incurs critical difficulties: the complex design of indoor structures, not to mention obstacles, necessitates time-consuming manual operation and resultantly huge
data sizes, which often leads to system slow-down or failure. To manage this problem, most of the recent and current research has looked to full automation; yet facility management personnel still rely on traditional field measurements because their qualitative results can only be obtained under ideal conditions or with some errors.
Alternatively, in this paper, a more practical semi-automatic methodology for improved productivity of asbuilt BIM creation with respect to large and complex indoor environments is proposed. The proposed approach
produces three-dimensional (3D) geometric drawings through three steps: segmentation for plane extraction,
refinement for removal of noisy points, and boundary tracing for outline extraction. The experimental results
for two test sites, a relatively simple corridor and a complex atrium, showed a high data-size reduction rate: to
3.8 and 4.3% of the original sizes, out of 51.5 and 111.5 million points, respectively. Based on the automatically
produced geometric drawings and the remaining points, manual as-built BIM creation was conducted. Using
the extracted lines as guides, each object and its relationship were more easily identified and modeled. At the
same time, the great reduction in the point clouds' data sizes enabled the modeler, using the BIM software, to efficiently manipulate the geometric drawing without system slow-down or failure. The proposed approach was
shown to be a potentially effective means of improving productivity and reliability in complex indoor as-built
BIM production