Semi-Procedural Textures using Point Process Texture Basis Functions
EGSR 2020 (Eurographics Symposium on Rendering)
CFG (Computer Graphics Forum)
Submission ID: 1018
Website In Progres...
Authors
P. Guehl (1), R. Allegre (1), J.-M. Dischler (1), B. Benes (2), and E. Galin (3)
- (1) ICube, Universite de Strasbourg, CNRS, France
- (2) Purdue University, USA
- (3) LIRIS, Université de Lyon, CNRS, France
Teaser
Input data, a single texture or multiple texture maps (a), and a binary structure (b) are used to generate a semi-procedural output (d). It is a novel texture representation where structure is procedural (d, top) and details are data-driven (d, bottom). Generated textures have procedural properties: infinity, no repetition, self-consistency, and genericity. The structure can be edited by using parameters (only three of them are shown here). Morphing is implicitly obtained by interpolating these parameters. The data-driven details guarantee a good visual match with the exemplar. We call Semi-procedural synthesis the synthesis from a structure that matches the input exemplar, and Semi-procedural editing the synthesis from a user edited structure. A rendered view of the input material is shown for comparison (c).
Abstract
We introduce a novel semi-procedural approach that avoids drawbacks of procedural textures and leverages advantages of data- driven 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.
Video
Submitted video to EGSR 2020 conference.
Video presentation at EGSR 2020 conference (modified version). A better version with better sound will be available soon!
Downloads
Code
Check out our dedicated github website: semiproctex
Acknowledgement
This work is supported by the HDWorlds project funded by the French National Research Agency (project ID: ANR-16-CE33-0001).
Bibtex
P. Guehl, R. Allègre, J.-M. Dischler, B. Benes, and E. Galin, Computer Graphics Forum , (2020).
@article {10.1111:cgf.14061, journal = {Computer Graphics Forum}, title = {{Semi-Procedural Textures Using Point Process Texture Basis Functions}}, author = {Guehl, Pascal and Allègre, Remi and Dischler, Jean-Michel and Benes, Bedrich and Galin, Eric}, year = {2020}, publisher = {The Eurographics Association and John Wiley & Sons Ltd.}, ISSN = {1467-8659}, DOI = {10.1111/cgf.14061} }