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Creating Large-Scale City Models from 3D-Point Clouds: A Robust Approach with Hybrid Representation
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Creating Large-Scale City Models from 3D-Point Clouds: A Robust Approach with Hybrid Representation
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Journal Article
Creating Large-Scale City Models from 3D-Point Clouds: A Robust Approach with Hybrid Representation
2012
Overview
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.
Publisher
Springer US,Springer,Springer Nature B.V,Springer Verlag
Subject
/ Analysis
/ Cities
/ Computer science; control theory; systems
/ Computer Vision and Pattern Recognition
/ Exact sciences and technology
/ Graphics
/ Grounds
/ Image Processing and Computer Vision
/ Lasers
/ Methods
/ Pattern Recognition and Graphics
/ Pattern recognition. Digital image processing. Computational geometry
/ Roofs
/ Studies
/ Vision
