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Picture Perception for Humans

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Introduction to Global Illumination Jack Tumblin CS 395 Advanced Computer Graphics Winter 2002 – PowerPoint PPT presentation

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Title: Picture Perception for Humans


1
Introduction to Global Illumination
Jack Tumblin CS 395 Advanced Computer
Graphics Winter 2002
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 directshadow
    ambientenvironment 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., SIGGRAPH98 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 gtgt ? (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.. SIGGRAPH94 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.. SIGGRAPH94 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.. SIGGRAPH94 Course
18 Fundamentals and Overview of Computer
Graphics
13
Review Surface Properties
  • Perfectly Diffuse
  • flat, chalky,

Incident LightRay
SurfaceNormal
Andrew Glassner et al.. SIGGRAPH94 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.. SIGGRAPH94 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 hemispheres 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 doesnt 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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