“Automated meshing of sparse 3D point clouds” by Cooper, Campbell and Gibson

  • ©Oli Cooper, Neill D. F. Campbell, and David Gibson




    Automated meshing of sparse 3D point clouds



    We propose a novel method that uses simulated annealing to create an optimal surface mesh by selecting a subset of a 3D point cloud and a triangulation that reliably represents the actual topology of the scene. This method provides a number of advantages: it copes well with noisy data, it produces a simplified mesh, particularly for scenes that contain many planes and, unlike greedy search techniques, it is much more likely to converge to a global minimum.


    1. MORRIS, D. D. AND KANADE, T. 2000. Image-consistent surface triangulation, CVPR, 1, 332–338.
    2. KREYLOS, O. AND HAMANN, B. 2001. On simulated annealing and the construction of linear spline approximations for scattered data, IEEE Transactions on Visualisation and Computer Graphics, 7, 1, 17–31.

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