Multichannel segmentation of planar point clouds using evolving curves

The paper deals with the multichannel curve segmentation of planar point clouds, scanned by a terrestrial laser scanner (TLS), which usually represent walls of buildings. Information derived from the point cloud can be used for quality check of a building (e.g. wall flatness or mutual perpendicularity of walls) or creation of virtual models of buildings. Therefore, segmentation of the planar point cloud into subsets representing the surface of the wall and other structures (e.g. door, electrical outlets) is desired. We describe a mathematical model of evolving planar curves, which is used for the segmentation of the point cloud. The evolution of curves is controlled by the properties of the scanned walls, such as colour and intensity. We discretize the model using the finite-volume method and the semi-implicit Inflow-Implicit/Outflow-Explicit (IIOE) scheme. We demonstrate the functionality of segmentation on real data.