Fast Depth-of-Field Rendering with Surface Splatting

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Fast Depth-of-Field Rendering with Surface
Splatting
Jaroslav Krivánek CTU PragueIRISA INRIA Rennes
Jirí Žára CTU Prague
Kadi Bouatouch IRISA INRIA Rennes
Computer
Graphics
Group
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Goal

• Depth-of-field rendering with point-based objects
• Why point-based ?
• Efficient for complex objects
• Why depth-of-field ?
• Nice and naturally looking images

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Overview

• Introduction
• Point-based rendering
• Depth-of-field
• Depth-of-field techniques
• Our contribution Point-based depth-of-field
  rendering
• Basic approach
• Extended method depth-of-field with level of
  detail
• Results
• Discussion
• Conclusions

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Point-based rendering

• Object represented by points without connectivity
• Point (surfel)
• position, normal, radius, material
• Rendering screen space surface reconstruction
• Efficient for very complex objects

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Depth-of-Field

• More naturally looking images
• Important depth cue for perception of scene
  configuration
• Draws attention to the focused objects

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Thin Lens Camera Model
VP
P
F/n
image plane
focal plane
lens
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Depth-of-Field Techniques in CG

• Supersampling
• Distributed ray tracing Cook et al. 1984
• Sample the light paths through the lens
• Multisampling Haeberli Akeley 1990
• Several images from different viewpoints on the
  lens
• Average the resulting images using accumulation
  buffer

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Depth of Field Techniques in CG

• Post-filtering Potmesil Chakravarty 1981
• Out-of-focus pixels displayed as CoC
• Intensity leakage, hypo-intensity
• Slow for larger kernels

Focus processor(filtering)
Image synthesizer
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Point-based rendering - splatting

• Draw each point as a fuzzy splat (an ellipse)

Image ? SPLATi
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Our Basic Approach

• Post-filtering

Focus processor(filtering)
Image with DOF
?i SPLATi depth
Image depth
Image ?i SPLATi
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Our Basic Approach
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Properties of our basic approach

• PROS
• Avoids leakage
• Reconstruction takes into account the splat depth
• No hypo-intensities
• Visibility resolved after blurring
• Handles transparency
• In the same way as the EWA splatting A-buffer
• CONS
• - Very slow, especially for large apertures
• A lot of large overlapping splats
• High number of fragments
• E.g. Lion, no blur 2.3 mil. blur 90.2 mil.
  (40x more)

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Our Extended Method

• Use Level of Detail (LOD) to attack complexity
• blur detail
• Select lower LOD for blurred parts
• of fragments increases more slowly
• E.g. Lion, no blur 2.3 mil. blur 5.3 mil.
  (2.3x more)

Blurred img.
Selected LOD
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Observation

• Selecting lower LOD for rendering equivalent to
  1) selecting the fine LOD 2)
  low-pass filtering is screen space
• Use LOD as a means for blurring
• not only to reduce complexity

Fine LOD
Lower LOD
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Effect of LOD Selection

• How to quantify the effect of LOD selection in
  terms of blur in the resulting image ?
• We use Bounding sphere hierarchy
• Qsplat Rusinkiewicz Levoy, 2000

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Bounding Sphere Hierarchy

• Building the hierarchy levels
  low-pass filtering subsampling

The finest level L0
Lower level L1
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LOD Filter in Screen Space

• GQL defined in local coordinates in object space
• GQL related to screen space by the local affine
  approximation J of the object-to-screen transform
• Selecting level L filtering in screen space by
  GJQLJT

GQL
GJQLJT
Screen space
Object space
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DOF with LOD - Algorithm

• Given the required screen space filter GQDOF
• Select LOD L such that support(
  GJQLJT ) lt support ( r ? GQDOF )
• Apply an additional screen space filter GQDIFF to
  get GQDOF

rDOF r ? GJQLJT ? GQDIFF
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Results
No Depth-of-Field everything in focus
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Results
Transparent mask in focus, male figure out of
focus
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Results
Male figure in focus, transparent mask out of
focus
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Results
Reference solution (multisampling)
Our algorithm

• Our blur looks too smooth because of the
  Gaussian filter

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Results
Reference solution (multisampling)
Our algorithm

• Artifacts due to incorrect surface
  reconstruction

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Discussion

• Simplifying assumptions limitations
• Gaussian distribution of light within the CoC
• Mostly ok
• We are blurring the texture before lighting
• We should blur after lighting
• Possible incorrect image reconstruction from
  blurred splats

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Conclusion

• A novel algorithm for depth of field rendering
• LOD as a means for depth-blurring
• Transparency
• Avoids intensity leakage
• Running time independent of the DOF
• - Only for point based rendering
• - A number of artifacts can appear
• Ideal tool for interactive DOF previewing
• Trial and error camera parameters setting

Acknowledgement Grant 2159/2002 MSMT Czech
Republic