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Communication Dans Un Congrès Année : 2020

Semi-Procedural Textures Using Point Process Texture Basis Functions

Résumé

We introduce a novel semi-procedural approach that avoids drawbacks of procedural textures and leverages advantages of datadriven texture synthesis. We split synthesis in two parts: 1) structure synthesis, based on a procedural parametric model and 2) color details synthesis, being data-driven. The procedural model consists of a generic Point Process Texture Basis Function (PPTBF), which extends sparse convolution noises by defining rich convolution kernels. They consist of a window function multiplied with a correlated statistical mixture of Gabor functions, both designed to encapsulate a large span of common spatial stochastic structures, including cells, cracks, grains, scratches, spots, stains, and waves. Parameters can be prescribed automatically by supplying binary structure exemplars. As for noise-based Gaussian textures, the PPTBF is used as stand-alone function, avoiding classification tasks that occur when handling multiple procedural assets. Because the PPTBF is based on a single set of parameters it allows for continuous transitions between different visual structures and an easy control over its visual characteristics. Color is consistently synthesized from the exemplar using a multiscale parallel texture synthesis by numbers, constrained by the PPTBF. The generated textures are parametric, infinite and avoid repetition. The data-driven part is automatic and guarantees strong visual resemblance with inputs.
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Dates et versions

hal-03162994 , version 1 (08-03-2021)

Identifiants

  • HAL Id : hal-03162994 , version 1

Citer

Pascal Guehl, Rémi Allegre, Jean-Michel Dischler, Bedrich Benes, Eric Galin. Semi-Procedural Textures Using Point Process Texture Basis Functions. EGSR (Eurographics Symposium on Rendering), Jun 2020, Londres, United Kingdom. ⟨hal-03162994⟩
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