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Position-free monte carlo simulation for arbitrary layered BSDFs
- Source :
- ACM Transactions on Graphics. 37:1-14
- Publication Year :
- 2018
- Publisher :
- Association for Computing Machinery (ACM), 2018.
-
Abstract
- Real-world materials are often layered: metallic paints, biological tissues, and many more. Variation in the interface and volumetric scattering properties of the layers leads to a rich diversity of material appearances from anisotropic highlights to complex textures and relief patterns. However, simulating light-layer interactions is a challenging problem. Past analytical or numerical solutions either introduce several approximations and limitations, or rely on expensive operations on discretized BSDFs, preventing the ability to freely vary the layer properties spatially. We introduce a new unbiased layered BSDF model based on Monte Carlo simulation, whose only assumption is the layer assumption itself. Our novel position-free path formulation is fundamentally more powerful at constructing light transport paths than generic light transport algorithms applied to the special case of flat layers, since it is based on a product of solid angle instead of area measures, so does not contain the high-variance geometry terms needed in the standard formulation. We introduce two techniques for sampling the position-free path integral, a forward path tracer with next-event estimation and a full bidirectional estimator. We show a number of examples, featuring multiple layers with surface and volumetric scattering, surface and phase function anisotropy, and spatial variation in all parameters.
- Subjects :
- Discretization
Computer science
Scattering
Monte Carlo method
Solid angle
Estimator
Sampling (statistics)
020207 software engineering
02 engineering and technology
01 natural sciences
Computer Graphics and Computer-Aided Design
010309 optics
Position (vector)
0103 physical sciences
Bidirectional scattering distribution function
Path (graph theory)
Path integral formulation
0202 electrical engineering, electronic engineering, information engineering
Monte Carlo integration
Statistical physics
Anisotropy
Subjects
Details
- ISSN :
- 15577368 and 07300301
- Volume :
- 37
- Database :
- OpenAIRE
- Journal :
- ACM Transactions on Graphics
- Accession number :
- edsair.doi...........ec8dc079bc85fee0cbc8d486fc28e5ec
- Full Text :
- https://doi.org/10.1145/3272127.3275053