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Direct Blue Noise resampling of meshes of arbitrary topology

Abstract : We propose in this paper a novel sampling method and an improvement of a spectral analysis tool that both handle complex shapes and sharp features. Starting from an arbitrary triangular mesh, our algorithm generates a new sampling pattern that exhibits blue noise properties. The fidelity to the original surface being essential, our algorithm preserves sharp features. Our sampling is based on a discrete dart throwing applied directly on the surface to get good blue noise sampling patterns. It is also driven by a feature detection tool - to avoid geometric aliasing. Experimental results prove that our sampling scheme is faster than techniques based on brute-force dart throwing, and produces sampling patterns with blue noise properties even for complex surfaces of arbitrary topology. In parallel, we also propose an improvement of a tool initially developed for the spectral analysis of non-uniform sampling patterns, that may generate biased results with complex shapes. The proposed improvement overcomes this problem.
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Contributor : Frédéric Payan <>
Submitted on : Tuesday, September 22, 2015 - 5:24:35 PM
Last modification on : Monday, March 29, 2021 - 3:16:11 PM
Long-term archiving on: : Tuesday, December 29, 2015 - 9:22:35 AM


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Jean-Luc Peyrot, Frédéric Payan, Marc Antonini. Direct Blue Noise resampling of meshes of arbitrary topology. Visual Computer, Springer Verlag, 2015, 31 (10), pp.1365-1381. ⟨10.1007/s00371-014-1019-1⟩. ⟨hal-01058835⟩



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