3D Building Model Reconstruction from Multi-view Aerial Imagery and Lidar Data

Abstract

A novel approach by integrating multi-view aerial imagery and lidar data is proposed to reconstruct 3D building models with accurate geometric position and fine details. First, a new algorithm is introduced for determination of principal orientations of a building, thus benefiting to improve the correctness and robustness of boundary segment extraction in aerial imagery. A new dynamic selection strategy based on lidar point density analysis and K-means clustering is then proposed to identify boundary segments from non-boundary segments. Second, 3D boundary segments are determined by incorporating lidar data and the 2D segments extracted from multi-view imagery. Finally, a new strategy for 3D building model reconstruction including automatic recovery of lost boundaries and robust reconstruction of rooftop patches is introduced. The experimental results indicate that the proposed approach can provide high quality 3D models with high-correctness, high-completeness, and good geometric accuracy.