21st International Meshing Roundtable
San Jose, CA
Department of Computer Science The University of Texas, Austin, TX, USA"
Many remeshing techniques sample the input surface in a meaningful way and then triangulate the samples to produce an output triangulated mesh. One class
of methods samples in a parametrization of the surface. Another class samples directly on the surface. These latter methods must have sufficient density of
samples to achieve outputs that are homeomorphic to the input. In many datasets samples must be very dense even in some nearly planar regions due to small
local feature size. We present an isotropic remeshing algorithm called CVT that achieves topological correctness while sampling sparsely in all flat regions,
regardless of local feature size. This is accomplished by segmenting the surface, remeshing the segmented subsurfaces individually and then stitching them
back together. We show that CVT produces quality meshes using fewer triangles than other methods. The output quality meshes are both homeomorphic and
geometrically close to the input surface.
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