Building Reconstruction using Manhattan-World Grammars

We present a passive computer vision method that exploits existing mapping and navigation databases in order to automatically create 3D building models. Our method defines a grammar for representing changes in building geometry that approximately follow the Manhattan-world assumption which states there is a predominance of three mutually orthogonal directions in the scene. By using multiple calibrated aerial images, we extend previous Manhattan-world methods to robustly produce a single, coherent, complete geometric model of a building with partial textures. Our method uses an optimization to discover a 3D building geometry that produces the same set of fa

• Type: Conference
• Year: 2010
• Where: CVPR
• Authors: Carlos Vanegas, Daniel Aliaga, Bedrich Benes
• Keywords: 3D Building, Building Geometry, Computer Vision, CVPR 2010, Vision Method