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Introduction to Global Illumination

Introduction to Global Illumination. Jack Tumblin CS 395 Advanced Computer Graphics Winter 2003. Global Illumination. Physical Simulation of Light Transport: Accuracy account for ALL light paths conservation of energy Prediction forward rendering calculate light meter readings

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Introduction to Global Illumination

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  1. Introduction to Global Illumination Jack Tumblin CS 395 Advanced Computer Graphics Winter 2003

  2. Global Illumination Physical Simulation of Light Transport: • Accuracyaccount for ALL light pathsconservation of energy • Predictionforward renderingcalculate light meter readings • Analysisinverse rendering! find surface properties ! • Realism?perceptually necessary?

  3. Local Illumination “Everything is lit by Light Sources” • Screen color = light source * surface reflectance • Refinements: reflectance = specular, diffuse, ambient, texture, … light = direct*shadow +ambient+environment maps, …

  4. Local Illumination “Everything is lit by Light Sources” • Refine: point light source  Area light source • Result? hard shadows  soft shadows

  5. Global Illumination “Everything is lit by Everything Else” • Screen color = entire scene * surface reflectance • Refinements: Models of area light sources, caustics, soft-shadowing, fog/smoke, photometric calibration, … H. Rushmeier et al., SIGGRAPH`98 Course 05 “A Basic Guide to Global Illumination”

  6. Global Illumination Idea: ALL POSSIBLE PATHS of light source to eye: From Jensen et al., SIGGRAPH2000 Course 20: ‘A Practical Guide To Global Illumination Using Photon Maps’

  7. Global Illumination Idea: ALL POSSIBLE PATHS of light source to eye: From Jensen et al., SIGGRAPH2000 Course 20: ‘A Practical Guide To Global Illumination Using Photon Maps’

  8. Limitations • Geometric Optics Only: • All objects, apertures >>  (wavelength) • YES: Reflection, Refraction, Scattering • No: fringes, diffraction, dispersion* (see movie) • Point-Based BRDF* (see Wann-Jensen et al.SIGGRAPH2001…

  9. Summary I Big Ideas: • Measure Light:Radiance • Measure Light Attenuation: BRDF • Light will ‘bounce around’ endlessly, decaying on each bounce:The Rendering Equation (intractable: must approximate)

  10. Review: Surface Properties Perfectly Specular: “Mirror” “infinite gloss” Phong Specular Model: L R cos() Incident LightRay SurfaceNormal ReflectedLight  Andrew Glassner et al.. SIGGRAPH`94 Course 18: “Fundamentals and Overview of Computer Graphics”

  11. Review: Surface Properties Slightly scattered Specular: “high gloss” Phong Specular Model: L R cos15() Incident LightRay SurfaceNormal ReflectedLight Andrew Glassner et al.. SIGGRAPH`94 Course 18: “Fundamentals and Overview of Computer Graphics”

  12. Review: Surface Properties More Scattered Specular: “medium gloss” Phong Specular Model: L R cos5() Incident LightRay SurfaceNormal Andrew Glassner et al.. SIGGRAPH`94 Course 18: “Fundamentals and Overview of Computer Graphics”

  13. Review: Surface Properties Perfectly Diffuse “flat”, “chalky”,… Incident LightRay SurfaceNormal Andrew Glassner et al.. SIGGRAPH`94 Course 18: “Fundamentals and Overview of Computer Graphics”

  14. Review: Surface Properties Most Materials: Combination of Diffuse and Specular Incident LightRay SurfaceNormal Andrew Glassner et al.. SIGGRAPH`94 Course 18: “Fundamentals and Overview of Computer Graphics”

  15. Point-wise Reflectance: BRDF Bidirectional Reflectance Distribution Function (i , i , r , r , i , r , …) == (Lr / Li) a scalar Illuminant Li Reflected Lr Infinitesimal Solid Angle  

  16. Point-wise Light: Radiance L Radiance: The Pointwise Measure of Light • Free-space light power L ==(energy/time) • At least a 5D scalar function:L(x, y, z, , , …) • Position (x,y,z), Angle (,) and more (t, , …) • Power density units, but tricky…

  17. Radiance Units Tricky: think Hemispheres with a floor: Solid Angle (steradians) =dS = fraction of a hemisphere’s area (4) Projected Area cos  dA  dA dA

  18. Rendering Equation (Kajiya 1986) . Radiance from point Radiance emitted from point Radiance reflected from point (from all inward directions)

  19. Rendering Equation Opportunities • Scalar operations only: () and L(), indep. of , x,y,z, , … • Linearity: • Solution = weighted sum of one-light solns. • Many BRDFs  weighted sum of diffuse, specular, gloss terms • SIGGRAPH2001 Result: reflected light = convolution(Lin, ) Difficulties • Almost no notrivial analytic solutions exist; MUST use approximate methods to solve • Verification: tough to measure real-world () and L() well • Notable wavelength-dependent surfaces exist (iridescent insect wings & casing, CD grooves) • BRDF doesn’t capture important subsurface scattering

  20. Implementation I • Practical Approximations: • Diffuse-only reflectance:Radiosity Solution Book presents old, slow, exact Gauss-Seidel… • Bounce-by-Bounce:Progressive Refinement, Path Tracing • Object-space Storage: Adaptive Meshing

  21. Remeshing Example

  22. Progressive Radiosity

  23. Implementation II • Practical Approximations: • From Both Ends:Bi-directional Tracing, • Trace from light to surfaces & store result, then • Trace from eye to surfaces • Scattering Rays where needed: • Monte-Carlo Methods, • Distributed Ray Tracing • Hybrids: • Numerical Methods (Galerkin, etc.), • Photon Maps, • Metropolis Transport, • Particles, Illumination caching, • 4D light volume sampling…

  24. Example: Photon Maps • Ideal: Trace Photon Paths • Trouble: high compute costs (exponential) • ‘Photon Maps’ A Hybrid Solution • ‘big, sticky, aggregate photons’ • Russian Roulette (reflect, transmit, absorb?) • Trace photons outwards from light sources • Store photons only at diffuse surfaces • Scattered data interp., • Cache photons/illum. at each step.

  25. Example: Photon Maps Forward-traced Reverse-TracedPhoton Map Result

  26. Photon Map Result • .

  27. Conclusion • Physically accurate (geometric optics only) simulation of light transport. • ‘Ultimate Realism’? perceptual, not physical • Languished as tweak-hungry lab curiosity • Gradual adoption for multitexturing source, for mixing real/synthetic images, Ph.Ds, theatre/architectural lighting, archaeology,… • Growing interest for use in inverse rendering tasks: image-based rendering & modeling

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