Radiance Cache Splatting: A GPU-Friendly Global Illumination Algorithm

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Radiance Cache SplattingA GPU-Friendly Global
Illumination Algorithm

• P. Gautron J. Krivánek
• K. Bouatouch S. Pattanaik

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Global Illumination
Why?
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Global Illumination
How?
Lo(P, ?o)
BRDF(?o, ?i) cos(?)d?i
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Global Illumination
How?
Lo(P, ?o)
BRDF(?o, ?i) cos(?)d?i
No analytical solution
Numerical methods
- Radiosity
- Photon mapping
- Path tracing
- Bidirectional path tracing
- Irradiance Radiance caching
-
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GPUs
Speed
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GPUs
Versatility
Linear algebra
Fluid dynamics
Signal processing
Databases

And graphics!
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Global Illumination GPUs
CPU
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Global Illumination GPUs
Previous work
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Contributions
A reformulation of (Ir)Radiance caching
- No complex data structure
- Fast, image-space (ir)radiance interpolation
- Fast approximation of hemisphere sampling
for fast and easy GPU implementation
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Outline
Introduction
Irradiance Radiance Caching
Our method Radiance Cache Splatting
Results
Conclusion Future Work
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Outline
Introduction
Irradiance Radiance Caching
Our method Radiance Cache Splatting
Results
Conclusion Future Work
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Irradiance Caching
Sparse computation of indirect diffuse lighting
?
?
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Irradiance Caching
Sparse computation of indirect diffuse lighting
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Irradiance Caching
Sparse computation of indirect diffuse lighting
Interpolation
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Interpolation
E
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Interpolation
S k / wk(P) gt 1/a
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Radiance Caching
Extension of irradiance caching to glossy
interreflections
Cache directional distribution of light
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Radiance Caching
Extension of irradiance caching to glossy
interreflections
Cache directional distribution of light
Hemispherical Harmonics
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Radiance Caching
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HSH Incident Radiance
HSH BRDF
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Implementation
Cache Record Computation
Ray tracing
?
?
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Implementation
Cache storage
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Outline
Introduction
Irradiance Radiance Caching
Our method Radiance Cache Splatting
Results
Conclusion Future Work
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(Ir)Radiance Caching vs GPU
(Ir)Radiance Caching
GPU
?
Ray tracing
Rasterization
Cache stored in tree
1/2/3D textures
Spatial queries
Texture lookups
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Reformulation
Our method
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Outline
Introduction
Irradiance Radiance Caching
Our method Radiance Cache Splatting
From octree to splatting
From ray tracing to rasterization
Overall algorithm
Results
Conclusion Future Work
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Outline
Introduction
Irradiance Radiance Caching
Our method Radiance Cache Splatting
From octree to splatting
From ray tracing to rasterization
Overall algorithm
Results
Conclusion Future Work
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From Octree to Splatting
Irradiance Interpolation
S k / wk(P) gt 1/a
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From Octree to Splatting
Irradiance Caching Weighting Function
Normals divergence
Distance
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From Octree to Splatting
Simplified Weighting Function
P
Pk
Normals divergence
Distance
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From Octree to Splatting
Simplified Weighting Function
P
Pk
Normals divergence
Distance
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From Octree to Splatting
Simplified Weighting Function
P
Pk
aRk
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From Octree to Splatting
Principle
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From Octree to Splatting
Principle
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From Octree to Splatting
Principle
wk(P)gt1/a ?
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From Octree to Splatting
Principle
wk(P)E(P)
wk(P)
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From Octree to Splatting
Principle
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From Octree to Splatting
Principle
wk(P)E(P)
wk(P)
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From Octree to Splatting
Final Image Generation
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From Octree to Splatting
Example
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Outline
Introduction
Irradiance Radiance Caching
Our method Radiance Cache Splatting
From octree to splatting
From ray tracing to rasterization
Overall algorithm
Results
Conclusion Future Work
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From Ray Tracing to Rasterization
CPU
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From Ray Tracing to Rasterization
GPU
Simple plane sampling
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From Ray Tracing to Rasterization
GPU
Simple plane sampling
??
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From Ray Tracing to Rasterization
GPU
Simple plane sampling
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From Ray Tracing to Rasterization
GPU
Simple plane sampling
Incoming radiance loss
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From Ray Tracing to Rasterization
GPU
Our plane sampling
??
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From Ray Tracing to Rasterization
GPU
Our plane sampling
Compensation of incoming radiance loss
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Our plane sampling
Summary
3x more accurate than simple plane sampling
Plausible directional information
Easy implementation on GPU
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Outline
Introduction
Irradiance Radiance Caching
Our method Radiance Cache Splatting
From octree to splatting
From ray tracing to rasterization
Overall algorithm
Results
Conclusion Future Work
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Algorithm
Step 1 information generation
GPU
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Algorithm
Step 2 detection
CPU
?
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Algorithm
Step 2 detection
CPU
GPU Hemisphere sampling
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Algorithm
Step 2 detection
CPU
GPU Hemisphere sampling
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Algorithm
Step 2 detection
CPU
?
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Algorithm
Step 2 detection
CPU
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Algorithm
Step 3 display
GPU
Matrices
Vertex Shader
Record information
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Algorithm
Step 3 display
GPU
Fragment Shader
Record information
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Algorithm
Step 3 display
GPU
Fragment Shader
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Algorithm
Summary
No spatial data structure
Spatial queries replaced by splatting
Interpolation by blending
No quality loss compared to (Ir)Radiance Caching
No order constraint for image traversal
Can be implemented using native GPU features
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Our renderer
Direct lighting
GPU per-pixel lighting shadow maps
CPU ray tracing
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Outline
Introduction
Irradiance Radiance Caching
Our method Radiance Cache Splatting
Results
Conclusion Future Work
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Results
Sibenik Cathedral (80K triangles)
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Results
Sponza Atrium (66K triangles)
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Results
Comparison with Radiance
Radiance Time
645 s
425 s
Our Renderer Time
13,7 s
14,3 s
Speedup
47,1
29,7
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Results
From Irradiance to Radiance Caching Venus (24K
triangles)
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Conclusion
Reformulation of (Ir)Radiance Caching
Speedup 29x 47x
Interactive or fast, high quality rendering
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Future Work
Multiple bounces
Area light sources
All-Frequency BRDFs
More complex models
Better hemisphere sampling
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Any questions?
Radiance Cache Splatting on the web
http//www.irisa.fr/siames/Pascal.Gautron/