Fast Depth-of-Field Rendering with Surface Splatting

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Fast Depth-of-Field Rendering with Surface Splatting. Jaroslav K ř ivánek CTU Prague IRISA – INRIA Rennes. Ji ř í Žára CTU Prague. Kadi Bouatouch IRISA – INRIA Rennes. Computer. Graphics. Group. Goal. Depth-of-field rendering with point-based objects Why point-based ? - PowerPoint PPT Presentation

Transcript of Fast Depth-of-Field Rendering with Surface Splatting

  • Fast Depth-of-Field Rendering with Surface Splatting Jaroslav KivnekCTU Prague IRISA INRIA RennesJi raCTU Prague Kadi BouatouchIRISA INRIA RennesComputerGraphicsGroup

  • GoalDepth-of-field rendering with point-based objectsWhy point-based ?Efficient for complex objectsWhy depth-of-field ?Nice and naturally looking images

  • OverviewIntroduction Point-based renderingDepth-of-fieldDepth-of-field techniquesOur contribution: Point-based depth-of-field renderingBasic approachExtended method: depth-of-field with level of detailResultsDiscussionConclusions

  • Point-based renderingObject represented by points without connectivity

    Point (surfel) position, normal, radius, material

    Rendering = screen space surface reconstruction

    Efficient for very complex objects

  • Depth-of-FieldMore naturally looking imagesImportant depth cue for perception of scene configurationDraws attention to the focused objects

  • Thin Lens Camera Modelimage planefocal planelensVPPF/n

  • Depth-of-Field Techniques in CGSupersamplingDistributed ray tracing [Cook et al. 1984]Sample the light paths through the lens

    Multisampling [Haeberli & Akeley 1990]Several images from different viewpoints on the lensAverage the resulting images using accumulation buffer

  • Depth of Field Techniques in CGPost-filtering [Potmesil & Chakravarty 1981]Out-of-focus pixels displayed as CoCIntensity leakage, hypo-intensitySlow for larger kernels

    Focus processor (filtering)Image synthesizer

  • Point-based rendering - splattingDraw each point as a fuzzy splat (an ellipse)Image = SPLATi

  • Our Basic ApproachPost-filteringFocus processor (filtering)Image + depthImage with DOFImage =i SPLATii SPLATi + depth

  • Our Basic Approach

  • Properties of our basic approachPROS+Avoids leakageReconstruction takes into account the splat depth+No hypo-intensitiesVisibility resolved after blurring +Handles transparencyIn the same way as the EWA splatting A-bufferCONS-Very slow, especially for large aperturesA lot of large overlapping splatsHigh number of fragments: E.g. Lion, no blur: 2.3 mil.; blur 90.2 mil. (40x more)

  • Our Extended MethodUse Level of Detail (LOD) to attack complexity blur = detailSelect lower LOD for blurred parts

    # of fragments increases more slowlyE.g. Lion, no blur: 2.3 mil.; blur 5.3 mil. (2.3x more)Blurred img.Selected LOD

  • ObservationSelecting 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 LODLower LOD

  • Effect of LOD SelectionHow to quantify the effect of LOD selection in terms of blur in the resulting image ?

    We use Bounding sphere hierarchy Qsplat [Rusinkiewicz & Levoy, 2000]

  • Bounding Sphere HierarchyThe finest level: L=0Lower level: L=1 Building the hierarchy levels low-pass filtering + subsampling

  • LOD Filter in Screen SpaceGQL defined in local coordinates in object spaceGQL related to screen space by the local affine approximation J of the object-to-screen transformSelecting level L = filtering in screen space by GJQLJTScreen spaceGQLGJQLJTObject space

  • DOF with LOD - AlgorithmGiven the required screen space filter GQDOF Select LOD L such that support( GJQLJT ) < support ( r GQDOF )Apply an additional screen space filter GQDIFF to get GQDOF

    rDOF = [r GJQLJT ] GQDIFF

  • ResultsNo Depth-of-Field everything in focus

  • ResultsTransparent mask in focus, male figure out of focus

  • ResultsMale figure in focus, transparent mask out of focus

  • ResultsOur algorithmReference solution (multisampling) Our blur looks too smooth because of the Gaussian filter

  • ResultsOur algorithmReference solution (multisampling) Artifacts due to incorrect surface reconstruction

  • DiscussionSimplifying assumptions & limitationsGaussian distribution of light within the CoC Mostly okWe are blurring the texture before lightingWe should blur after lightingPossible incorrect image reconstruction from blurred splats

  • ConclusionA novel algorithm for depth of field renderingLOD 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 appearIdeal tool for interactive DOF previewingTrial and error camera parameters settingAcknowledgement: Grant 2159/2002 MSMT Czech Republic