Planar segmentation and topological reconstruction for urban buildings with lidar point clouds

Abstract

This paper presents a framework for segmentation and topological relationship reconstruction of building planar surfaces by using airborne LiDAR point clouds. The analysis of a planar surface structure is fundamental to almost any applications involving LiDAR data, especially building reconstruction. The proposed framework consists of two steps. Firstly, point clouds is segmented using an improved RANSAC (RANdom SAmple Consensus) algorithm with variant consensus set threshold. It is designed to solve under- or no- segmentation problem. It reduces consensus set threshold when the original RANSAC could not find valid planes, hence small planar surfaces would be extracted. Then, the topological relationship planar surface is constructed based on estimating connectedness of connecting point pairs between each pair of adjacent planar surfaces. The types of connectedness of planar surface are divided into three categories and a statistical method is used to estimate the connectedness type. The reconstructed topological relationship is described by an adjacent graph and can be utilized in the building modeling. Experiments show the effectiveness and efficiency of the proposed framework.