Georgios (George) Papaioannou Dept. of Computer Science Athens University of Economics & Business
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Georgios (George) Papaioannou
Dept. of Computer ScienceAthens University of Economics & Business
HPG 2011
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Motivation
• Why build yet another RTGI method?– Significant number of existing techniques– RSM, CLPV, VBGI etc
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Motivation
• Why build yet another RTGI method?– Significant number of existing techniques– RSM, CLPV, VBGI etc
• Wanted a diffuse GI method that:– Is stable enough (no view dependence, no
flickering etc)– Can capture multiple light bounce effects– Is fast enough to be of practical use– Has limited requirements easy to integrate to
rendering engines
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Main Idea
• Why not combine the benefits of existing methods? • RT Radiance Caching
– Fast to sample – Stable
• But use Reflective Shadow Maps to populate RC– Cheap creation (additional data in SM MRTs)– Camera view independent– Good scaling (e.g. importance sampling)
• Additional functionality for multiple bounces and occlusion
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Method Outline
For all Radiance Hints (all RH volume texels):
- Sample RSM radiance and encode it as SH
For all Radiance Hints (all RH volume texels): - Sample RH volume for sec. bounce radiance
Repeat forall RSMs
For each (visible) geometry fragment sample RH
volume to reconstruct GI
Radiance field estim
ation GI rendering
Repeat for2…N bounces
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
RH Configuration
RH points are the nodes of a 3D grid
The grid covers any part of the scene
Extents of each RH grid cell
RSM data (position, flux, normals)
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
RSM Sampling
Sample from random points inside the cell
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
RSM Sampling
Accepted samples
Rejected samples
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Radiance Encoding
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Radiance Encoding
RH radiance is encoded as spherical harmonics
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Radiance Encoding
With up to 8 MRTs:
4- and 9-coefficient spherical harmonics can encode RGB radiance field
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Comments: RH Sample Distribution
• Uniform distribution of sample points in RH cell• Why?
– There is nothing special about RH location!– It should be representative of entire cell volume
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Min and Max RSM Sample Distances
• For reasons that will become apparent next, also maintain and store for each RH:– Min distance to RSM sample– Max distance to RSM sample
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Comments: Multiple RSMs
• For multiple RSMs (multiple/omni-directional):– A fixed number of samples is distributed among
RSMs– Ideal for importance sampling of light sources
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Secondary Bounces
Geometry-less:
Randomly sample the radiance field!
c
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Secondary Bounces
Interpolate SH from nearest RHs (volume texture tri-linear interpolation)
Integrate incident radiance on the hemisphere aligned with d:
“reflected” radiance on an imaginary surface aligned with d
d
pRH
q
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Secondary Bounces: RH Reliability
• Are all random RH samples equally reliable?– Certainly not !– RH near surfaces are more reliable must be
favored– But …we know nothing about the geometry
• Solution:
– For each RH, use the minimum distance rmin from RSM sample positions
– Bias RH contribution using rmin
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Secondary Bounces: RH Reliability
Min distance to RSM samplesInterpolated min distance at arbitrary location
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Diffuse GI Reconstruction
• Directly sample the RH volume textures at 4 locations in a rotating kernel above the surface
• Perform integration in SH domain over the surface-aligned hemisphere
Voxel diagonal
Half voxel diagonal
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Direct illumination 1st bounce
2nd bounce (total 11.6ms) Path tracing
A Simple Example
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Occlusion
• What about visibility tests?– RSMs alone are not very helpful
• Store “blocking” information? Trying to avoid: – View-dependent geometry injection– Volume-based occlusion. Can be slow to
generate and requires multiple texture reads per sample
• Can I use existing data?– Yes, but only in secondary bounces– Special treatment for first bounce
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Secondary Bounce Occlusion• We can use a probabilistic (heuristic) attenuation metric
using the stored min/max distances
RHnp
RHjp
1
Visibility
0
RH ,minnrRH ,maxnrRH ,minjrRH ,maxjr
RH ,max RH ,maxn jr rRH ,min RH ,minn jr r
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Secondary Bounce Occlusion Example
• The secondary bounce attenuation is not as important as the first bounce one but is almost for free.
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
What About First-Bounce Occlusion?
• Most important occlusion stage• Large RSM scene coverage “masks” occlusion (but
results are still far from ground truth)• Small RSM scene coverage leads to erroneous
cases:
Wall not present in RSM
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Depth-based Occlusion (Extension)
• Use camera depth map to intercept RSM samples• Uses a voting system to attenuate RSM samples:• Test a few points on the RH-RSM line of sight
against the depth map
2/6 visible
4/6 visible
6/6 visible
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Depth-based Occlusion (Extension)
• View-dependent, but:• Not a binary visibility test ! Time-coherent
No occlusion Depth-based attenuation
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Performance
GI reconstruction
2nd bounce
RH generation
GI reconstruction
2nd bounce
RH generation
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Examples – No 1st Bounce Occlusion
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Examples - No 1st Bounce Occlusion
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Examples - With 1st Bounce Occlusion
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Input and Requirements
• Just the light source RSMs (modern rendering engines require them for other tasks anyway)
• No geometry is rendered during GI calculations• No geometry shaders are needed• No pre-processing of any kind• No post-processing
• Can be used in direct and deferred renderers
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Other Extensions
• Small RH volumes can be placed in disjoint locations – More effective coverage of important areas– Nested RH volumes (for more detail)
• Due to their linear form (SHs, distances), RHs can be automatically mip-mapped and hierarchically sampled
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Pros and Cons
• The good news are:– Yes, it is versatile and easy to configure– Has minimal requirements– Handles multiple bounces– The (core) method is view-independent
• But:– Is an approximate approach– Heuristically handles occlusion
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Real-Time Diffuse Global Illumination Using Radiance Hints HPG2011
Thank You
• Please visit the AUEB Graphics Group web site (http://graphics.cs.aueb.gr) for:– Shader source code– Additional demo images and videos
• A complete mathematical analysis can be found in the paper.