Structure Reconstruction of Indoor Scene from Terrestrial Laser Scanner

Abstract

Indoor scene reconstruction from point cloud data provided by Terrestrial laser scanning (TLS) has become an issue of major interest in recent years. However, the raw scanned indoor scene is always complex with severe noise, outliers and incomplete regions, which produces more difficulties for indoor scene modeling. In this paper, we presented an automatic approach to reconstruct the structure of indoor scene from point clouds acquired by registering several scans. Our method first extracts different candidate walls by separating the indoor scene into different planes based on normal variation. Then the boundary of those candidate walls are obtained by projecting them onto 2D planes. We classify the walls into exterior wall and interior wall by clustering. After distinguishing the 3D points belonging to exterior walls, a simple strategy is generated to refine the 3D model of wall structure. The methodology has been tested on three real datasets, which constitute of different varieties of indoor scenes. The results derived reveal that the indoor scene could be correctly extracted and modeled.