Gaussian Sphere sampling based Surface Approximation
نویسندگان
چکیده
Sampling of 3D meshes is at the foundation of any surface simplification technique. In this paper, we use the recent results on quantization and surface approximation theory to propose a simple, robust, linear time, output sensitive algorithm for sampling meshes with the purpose of surface approximation. Our algorithm is based on the mapping of regular sampling and triangulation of the Gaussian sphere onto a manifold surface. An interesting aspect of our algorithm is that we do not explicitly measure, minimize, or prioritize any error to simplify and do not explicitly cluster the faces to find proxies, but still achieve bounded error approximation of the shape.
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