A Residential Building Reconstruction Method and Its Evaluation

A novel method for three-dimensional (3D) residential building reconstruction in urban areas using LiDAR (light detection and ranging) data is proposed. The main contribution of this work is the automatic segmentation of roof points and roof type recognition and reconstruction based on sparse LiDAR data. Using minimum bounding rectangle (MBR) method and model-based reconstruction, we are able to automatically identify individual buildings from cluttered residential areas and re-create building models with improved accuracy in a reasonably short time. We applied our method to urban sites in the city of New Orleans and demonstrated that the method identified building measurements successfully from LiDAR data and rebuilt 3D models effectively. Our experiments show that even in the presence of noise we can successfully reconstruct small buildings given relatively sparse LiDAR samples with help from template databases.