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Towards a Taxonomy of Global Illumination Algorithms Philip Dutré Program of Computer Graphics Cornell University.

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Presentation on theme: "Towards a Taxonomy of Global Illumination Algorithms Philip Dutré Program of Computer Graphics Cornell University."— Presentation transcript:

1 Towards a Taxonomy of Global Illumination Algorithms Philip Dutré Program of Computer Graphics Cornell University

2 Global Illumination Make a photo-realistic picture of a virtual scene which is physically-based modeled (source: Stroebel ‘86)

3 Photo-realistic picture? Picture = matrix of ‘light intensity’ values Rendered picture and photograph look the same to a human observer

4 Physically-based modeled? Light Sources Emission characteristics Materials Reflectance characteristics (BRDF) Geometry

5 Rendering Framework emission geometry BRDF radiometric values displayed image goniometric error metric radiometric error metric perceptual error metric radiometric comparisonperceptual comparison = ? Visual DisplayLight Transport Simulation 2727 1515 1313 2 = ? 9 9 14 1 7 7 9 7 5 5 7 9 5 5 5 7 10 11 12 2 6 8 10 9 4 4 8 9 6 5 5 6 goniometric comparison Display Observer

6 Light Transport Light Transport Simulation Radiometric Values “Intensity” for each point and each direction Emission (light sources) BRDFs (materials) Geometry (objects)

7 Global Illumination Problem eye pixel What is the ‘intensity’ of this surface in the direction of the eye?

8 Global Illumination Problem What is the ‘intensity’ of this surface in all possible directions?

9 Common Ground for GI Pre-’86: ??? 1986: Rendering Equation 1992: Potential Equation Is there a single framework that describes all GI algorithms?

10 Radiance (L) Fundamental transport quantity … power per unit projected area per solid angle in each point and direction Radiance is invariant along a straight line (that’s why ray tracing works) Flux = integrated radiance

11 Radiance Distribution Look for initial L (light sources) Propagate L along straight paths to the first visible surfaces Reflect L locally at the surfaces Light source descriptions Visibility calculation (geometry) Reflectance (materials)

12 Radiance Distribution Propagate...… and reflect

13 Shooting Operation Propagation + Reflection = “Shooting” L new = SL init … propagate and reflect again!

14 Shooting Operation … and reflect again… propagate

15 Shooting Operation L newer = SL new = SSL init L total = L init +SL init +SSL init

16 Shooting Operation LiLi SL i SSL i SSSL i L i +SL i L i +SL i +SSL i L i +SL i + SSL i + SSSL i LiLi

17 Shooting Equilibrium L equil = L init +SL equil Rendering Equation

18 Collecting Radiance Collect all radiance at this patch (= flux) How do we know where to collect radiance?

19 Collecting Radiance Define an importance function W W = 1 where to collect W = 0 where not to collect Each patch/pixel/… has its own W

20 Collecting Radiance W = 1 W = 0 Flux = Radiance L x Importance W =

21 “Helmholtz” Reciprocity Role of source and receiver can be switched, flux does not change

22 Dual Transport Instead of shooting from light sources and collecting at receivers … … start at receivers and trace back to the light sources

23 Dual Transport Start at surface with W init = 1 “Where could radiance come from?” reflect W locally propagate reflected W backwards Collect propagated W at light sources

24 Dual Transport W init …reflect back…propagate back W new = RW init

25 Dual Transport W equil = W init +RW equil Importance Equation

26 Dual Transport Collect propagated W at light sources L i 0 at light sources = Flux = Importance W x Radiance L init

27 Solving Global Illumination Shoot radiance from light source and collect at receiver Shoot importance from receiver and collect at light sources or … shoot both at once and collect in the middle

28 Solving Global Illumination

29 F = + or or or +

30 Ray Tracing = Shoot W

31 Particle tracing = Shoot L

32 Bidirectional tracing = shoot both

33 *Tracing F = + or or or + Particle Tracing Ray Tracing BT

34 Bidirectional Path Tracing (RenderPark 98)

35 Radiosity Progressive radiosity = shooting L Gauss-Seidel = shooting W Bidirectional Radiosity shoot L and W and meet in the middle select each patch in turn as W-source faster convergence for selected patches

36 Bidirectional Radiosity

37 Algorithms Ray Tracing Particle tracing Bidirectional path tracing Gauss-Seidel radiosity Progressive radiosity Bidirectional Radiosity

38 Conclusion Framework for global illumination Combines radiance and potential in a single formulation Taxonomy of algorithms Bidirectional algorithms


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