A Fast Algorithm for Boundary Point Extraction of Planar Building Components from Point Clouds

The boundaries of planar building components characterize the structural outline of buildings and are of great importance in applications such as indoor model reconstruction and localization. However, traditional methods for extracting boundary points of planar building components from point clouds are often constrained by high computational complexity, limited efficiency, and insufficient accuracy. To address these challenges, this paper presents a rapid algorithm for the direct extraction of boundary points from point cloud data. The algorithm first performs planar fitting and projects all points onto the fitted plane to mitigate the influence of outlier noise. Next, for each point in the point cloud, a plane is constructed perpendicular to the existing plane points. Coarse boundary points are identified by counting the neighboring points on one side of this plane, which effectively eliminates most of the interior points. Finally, a boundary detection zone is defined for each coarse boundary point and its neighboring points. The precise boundary points are extracted by counting the number of points within this defined region. Experimental validation indicates that our algorithm can extract boundary points of planar building components from point clouds both accurately and efficiently, with notable robustness against noise.