As we begin to consider modeling large, realistic 3D building scenes, it becomes necessary to consider a more compact representation over the polygonal mesh model. Due to the large amounts of annotated training data, which is costly to obtain, we leverage synthetic data to train our system for the satellite image domain. By utilizing the synthetic data, we formulate the building decomposition as an application of instance segmentation and primitive fitting to decompose a building into a set of primitive shapes. Experimental results on WorldView-3 satellite image dataset demonstrate the effectiveness of our 3D building modeling approach.
@article{arxiv.1901.05554,
title = {Primitive-based 3D Building Modeling, Sensor Simulation, and Estimation},
author = {Xia Li and Yen-Liang Lin and James Miller and Alex Cheon and Walt Dixon},
journal= {arXiv preprint arXiv:1901.05554},
year = {2019}
}