Creating large-scale city models from 3D-point clouds: a robust approach with hybrid representation
Résumé
We present a novel and robust method for modeling cities from 3D-point data. Our algorithm pro- vides a more complete description than existing ap- proaches by reconstructing simultaneously buildings, trees and topologically complex grounds. A major con- tribution of our work is the original way of model- ing buildings which guarantees a high generalization level while having semantized and compact represen- tations. Geometric 3D-primitives such as planes, cylin- ders, spheres or cones describe regular roof sections, and are combined with mesh-patches that represent irregu- lar roof components. The various urban components in- teract through a non-convex energy minimization prob- lem in which they are propagated under arrangement constraints over a planimetric map. Our approach is ex- perimentally 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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