Acceleration of Monte Carlo Path Tracing in General Environments GGG speech

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Acceleration of Monte Carlo Path Tracing in General Environments GGG speech

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Account for links arriving to leaf clusters with media and sample directions as for surfaces ... Strange bugs... Avoid code duplication, scene duplication ... –

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Title: Acceleration of Monte Carlo Path Tracing in General Environments GGG speech


1
Acceleration of Monte Carlo PathTracing in
General EnvironmentsGGG speech
Frederic Pérez1Ignacio Martín1François X.
Sillion2Xavier Pueyo1
2
Outline
  • Importance Sampling
  • Previous work
  • Link Probabilities
  • Results
  • Conclusions
  • Future Work
  • Current Work
  • The new SIR

3
Importance Sampling
  • Variance reduction technique
  • Use the best samples to evaluate an integral
    Probability Density Function (PDF) prop. to
    kernel
  • Reflectance equation
  • Importance sampling
  • Use of approximate for PDF ?
    Usually by means of a 1st pass

4
Previous Work
  • Chen et al. 91
  • Progressive Multi-Pass
  • Jensen 95
  • Importance Driven Path Tracing using the Photon
    Map
  • Szirmay-Kalos et al. 98
  • Importance Driven Quasi-Random walk
  • StĂĽrzlinger 96, Ureña Torres 97
  • Final Gathering

5
Shortcomings
  • Fixed subdivision of hemisphere
  • Cannot adapt to irradiance changes
  • Missing samples
  • Sources does not fit solid angles
  • Fixed subdivision of object space first pass

6
Shortcomings
  • Smallprojections

? Wasting samples
? Bad PDF
7
Link Probabilities Overview
  • 1st Pass Radiance Clustering
  • Produces Line-Space hierarchy Links
  • Coarse solution not for rendering
  • 2nd Pass Monte Carlo Path Tracing
  • Improved Importance Sampling with Link
    Probabilities
  • Use links arriving at leaves as a representation
    of the irradiance

8
Link Probabilities Basic Algorithm
  • Importance Sampling in a random walk step

for each bounce at point x
x
9
Link Probabilities PDF per leaf?
  • Using a PDF per leaf ? Artifacts for 1st
    bounce

? Solution Recompute PDF per pixel
10
Link Probabilities
  • Link overlap

S2
S1
y
? Check if links sender is hit
11
Link Probabilities
  • PDF accuracy and visibility

S1
l1
S2
l2
R
Finite elements pass ? two links arriving at
leaf R
12
Link Probabilities
  • PDF accuracy and visibility

Solution Adaptive PDFs
13
Results
  • Simple test scene

14
Results
  • Room with indirect illumination

15
Results
16 samples
128 samples
64 samples
NEE
806s
1613s
201s
LP
1273s
2434s
409s
16
Conclusions
  • Enhancement of Path Tracing by Importance
    Sampling based on the estimated irradiances
    computed with a Radiance Clustering 1st pass
  • Quality of the images doesnt strongly depend on
    the lighting conditions

17
Future Work
  • Extension for isotropic participating media
  • Account for links arriving to leaf clusters with
    media and sample directions as for surfaces
  • Addition of glossy surfaces and anisotropic
    participating media
  • Account for BRDF/phase function
  • Use of Link Probabilities in BPT
  • Eye paths as presented
  • Light paths similarly using importance
  • Comparison to Metropolis Light transport

18
Acknowledgments ( the paper)
  • SIMULGEN ESPRIT project 35772
  • http//iiia.udg.es/Simulgen
  • Generalitat de Catalunyas AIRE
  • CICYTs TIC98-0586-C03-02
  • The paper
  • http//ima.udg.es/frederic/publications.html

19
Current Work
  • New code Getting rid of BRIGHT SIR
  • Finishing the implementation over the old code
    estimated to be harder than re-starting
  • The old software was hard to maintain
  • Strange bugs...
  • Avoid code duplication, scene duplication ? work
    with a more compact and efficient system? new
    SIR

20
Current Work New Two Pass Method
  • New code using the new SIR
  • New 1st pass particle tracing based
  • Same requirements as previous 1st pass
  • Obtain quickly a coarse solution to guide a 2nd
    pass
  • Maintaining the 2nd pass using the Link
    Probabilities
  • Reimplementing and finishing it

21
Current Work New 1st Pass
  • Extended Hierarchical Monte Carlo Radiosity ?
    Link hierarchy
  • Bekaert et al. Hierarchical Monte Carlo
    Radiosity. In Rendering Techniques 98
  • Adaptively refined mesh and (implicit) link
    structure ? but storing links for the 2nd pass
  • Extended for anisotropic participating media and
    glossy surfaces ? by means of Illumination Samples

22
Current Work Snapshot
  • Implementation
  • As in Bekaerts (RenderPark)
  • Breadth-first MCR ? Push-pull only after drawing
    all samples
  • Local Monte Carlo
  • Currently almost finished for diffuse surfaces
  • To do
  • Finish it for diffuse surfaces
  • Implement participating media
  • Reimplement second pass

23
Current Work First Results
24
The new SIR
  • http//ima.udg.es/sir/
  • Using GNU configure/build
  • Self documented using doxygen
  • Reference guide style
  • Dependency graphs
  • tkcvs web access commit ? news!
  • Based on triangles (so far)
  • GTK as GUI
  • GTS to triangulate (instead of CDT)
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