Abstract
We present a novel and robust method for modeling cities from 3D-point data. Our algorithm provides a more complete description than existing approaches by reconstructing simultaneously buildings, trees and topologically complex grounds. A major contribution of our work is the original way of modeling buildings which guarantees a high generalization level while having semantized and compact representations. Geometric 3D-primitives such as planes, cylinders, spheres or cones describe regular roof sections, and are combined with mesh-patches that represent irregular roof components. The various urban components interact through a non-convex energy minimization problem in which they are propagated under arrangement constraints over a planimetric map. Our approach is experimentally validated on complex buildings and large urban scenes of millions of points, and is compared to state-of-the-art methods.
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Lafarge, F., Mallet, C. Creating Large-Scale City Models from 3D-Point Clouds: A Robust Approach with Hybrid Representation. Int J Comput Vis 99, 69–85 (2012). https://doi.org/10.1007/s11263-012-0517-8
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DOI: https://doi.org/10.1007/s11263-012-0517-8