Linear efficient antialiased displacement and reflectance mapping

Author:

Dupuy Jonathan1,Heitz Eric2,Iehl Jean-Claude3,Poulin Pierre4,Neyret Fabrice5,Ostromoukhov Victor3

Affiliation:

1. Université de Montréal and LIRIS, Université Lyon 1

2. INRIA/LJK and Université de Montréal

3. LIRIS, Université Lyon 1

4. Université de Montréal

5. INRIA/LJK

Abstract

We present Linear Efficient Antialiased Displacement and Reflectance (LEADR) mapping, a reflectance filtering technique for displacement mapped surfaces. Similarly to LEAN mapping, it employs two mipmapped texture maps, which store the first two moments of the displacement gradients. During rendering, the projection of this data over a pixel is used to compute a noncentered anisotropic Beckmann distribution using only simple, linear filtering operations. The distribution is then injected in a new, physically based, rough surface microfacet BRDF model, that includes masking and shadowing effects for both diffuse and specular reflection under directional, point, and environment lighting. Furthermore, our method is compatible with animation and deformation, making it extremely general and flexible. Combined with an adaptive meshing scheme, LEADR mapping provides the very first seamless and hardware-accelerated multi-resolution representation for surfaces. In order to demonstrate its effectiveness, we render highly detailed production models in real time on a commodity GPU, with quality matching supersampled ground-truth images.

Funder

Natural Sciences and Engineering Research Council of Canada

Networks of Centres of Excellence of Canada

Agence Nationale de la Recherche

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design

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3. Effect of correlation between shadowing and shadowed points on the Wagner and Smith monostatic one-dimensional shadowing functions

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