Fast Global Illumination Including Specular Effects - PowerPoint PPT Presentation

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Fast Global Illumination Including Specular Effects

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Specular Effects Xavier Granier 1 George Drettakis 1 Bruce J. Walter 2 1 iMAGIS -GRAVIR/IMAG-INRIA iMAGIS is a joint project of CNRS/INRIA/UJF/INPG – PowerPoint PPT presentation

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Title: Fast Global Illumination Including Specular Effects


1
Fast Global Illumination IncludingSpecular
Effects
2
Motivation
  • Realistic Illumination
  • All light paths
  • Time-Quality Tradeoff
  • Interactive Visualisation
  • Quality Control

3
Talk overview
  • Previous work
  • New Integrated Algorithm
  • Results
  • Conclusion

4
Previous Work
  • Deterministic methods
  • Radiosity Goral84,Cohen88,etc
  • Hierarchy and Clustering Hanrahan91, Smits94,
    Sillion95, etc
  • Non diffuse Immel86, Sillion89, Sillion91, etc
  • Probabilistic
  • Photon Map Jensen96,etc
  • Density Estimation Walter97,etc

5
Previous Work
  • Multi-pass
  • Two-pass Wallace97,Sillion89,etc
  • Integrated Chen91,etc
  • Interactive viewing
  • Render-Cache Walter99
  • Directional Storage Stamminger99,etc

6
Overview
D Diffuse and S Non Diffuse
  • DD transfer
  • Hierarchical Radiosity with Clustering (HRC)
  • DSD transfer
  • Particle tracing during HRC gather

Images have specular path to eye added by
Ray-Tracing
7
Algorithm Overview
  • Construct hierarchy
  • Hierarchy elements clusters and surfaces
  • For each iteration
  • Refine
  • Gather - Energy transfer
  • particle emission restricted by links
  • Push-pull
  • particle placement

8
Refinement
  • Link placement
  • Choose appropriate hierarchy level for transfer
  • Refinement test Energy lt e
  • Visibility classification and computation
  • Shafts and blocker lists for classification/optimi
    sation
  • Unoccluded form factor computation

9
Energy transfer through a link
  • Diffuse-Diffuse transfer

IRS Radiosity x Form Factor x Visibility
IR IR IRS
10
Energy transfer through links
  • Diffuse-Specular transfer
  • Diffuse-Specular transfer
  • Probabilistic emission of particles
  • Reflection on receiver
  • Propagation and impact storage
  • Links guide particles
  • Links encode light flow
  • Restrict number of particles

11
Particle Emission
  • Number of particles
  • Flux S to R/ Constant energy
  • Uniform sampling
  • Inverse of (Measure(R) x Measure(S))
  • Particle power
  • Flux from s to r corrected by
  • number of particles and
  • probability of sample choice

12
Push-Pull
  • Push Hierarchy descent
  • Particle placement
  • Integrate particle power into irradiance
  • Radiosity computation on leaves
  • Pull Radiosity averaging

13
Particle Placement
  • Detect high variation and concentration
  • Quantity
  • Average position and "Spread Factor"
  • Push particle if
  • High concentration and high energy

14
Interactive Visualisation
  • Computed Solution Diffuse part
  • View independant solution
  • Hardware rendering
  • Ray Trace View dependant part
  • Save image
  • Interactivity Render - Cache

15
Results Quality control
Vary ?ct parameter
4 sec 1200 particles
5 sec 7800 particles
15 sec 81800 particles
16
Indirect
1 min 42 sec
4 min 34 sec
17
Particle tracing comparison
Complex, indirectly lit scenesimulation ? 10 min
18
Video
VIDEO
19
Conclusion
  • Integrated algorithm
  • Hierarchical Radiosity with Clustering and
    Particle Tracing
  • Handles indirect light well
  • Guide particle trace with Links
  • Place particles during push-pull
  • Rapid computation
  • Interactive simulations for small scenes
  • Fast coarse solutions for complex scenes

20
Future Work
  • Separate Reconstruction
  • Low and High frequencies
  • Dynamic updates
  • Partial particle shooting
  • Distributed/Monte-Carlo Ray-trace
  • Solution with importance
  • Local precise solution
  • Detect needed interactions

21
The End
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