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Volume Rendering Zoo#


  • Reference pathtrace/raymarch
  • Volume Flipbook
  • Particle Rendering with Slabs sampling
  • Channel Lighting
  • Volume Filtering with mips
  • Turn Zeus into Cloud Volume
  • IsoSurface Tracking
  • Mean Occlusion
  • Directional Occlusion
  • Directional Lightfield
  • Vertex Baking
  • Basis Functions
  • Spherical Harmonics
  • Spherical Gaussians
  • Fourier Opacity Maps
  • Extinction Transmittance Maps [Extinction Transmittance Maps]

  • Precomputed Radiance Transfer for Volume Rendering

  • Do it inside the volume
  • Can also do it on the surface and tangent basis (use burley's normalized diffusion profile as it provides super simple artistic control)

    • Reference: Approximate Reflectance Profiles for Efficient Subsurface Scattering
    • Reference: Extending the Disney BRDF to a BSDF with Integrated Subsurface Scattering
  • Multiple Scattering approximations

  • Contrast approximation for art directable multiple scattering

    • Oz: The Great and Volumetric
    • Art-Directable Multiple Volumetric Scattering
    • Technique is basically exponentiation of single scattering with multiple octaves
    • Must make sure \(a \leq b\) to be energy conserving
      left(x, omega_{i}right)=sum_{0}^{(N-1)} L operatorname{scat}left(x, omega_{i}right) \
      begin{aligned} sigma_{s}^{prime} &=sigma_{s} times a^{n} \
      sigma_{e}^{prime} &=sigma_{e} times b^{n} \
      p^{prime}(theta) &=pleft(theta times c^{n}right) end{aligned}
  • Take Mean Free Path/Transport mean free path into account

  • The scattering mean free path is the average distance between scattering events (in biological tissues around 100 μm)
  • The transport mean free path can be thought of as the mean distance after which a photon’s direction becomes random (in biological tissues around 1 mm)
  • The transport length in a strongly diffusing medium (noted l*) is the length over which the direction of propagation of the photon is randomized. It is related to the mean free path l by the relation

  • NiceToHave Incorporate Baked VLM#

  • VolumetricFog.usf: LightScatteringCS() - GetVolumetricLightmapSH2(BrickTextureUVs);
  • Radiance caching gradients
  • A Novel Sampling Algorithm for Fast and Stable Real-Time Volume Rendering:
  • Amanatide ray marching: A Fast Voxel Traversal Algorithm for Ray Tracing

  • Linearly transformed cosines

  • Use them as a basis. Linear transform of cosine lobe (scale, skew, rotation) doesn't affect integral product and has closed form solution
  • GPU Zen Chapter: Linear-Light Shading with Linearly Transformed Cosines

Todo Tasks#

  • Create ShowcaseZoo
  • Reference
  • Particle Slab
  • Penny Channel Lighting
  • Skull & Bones Channel Lighting
  • IsoMesh Basis Rendering

  • Channel Lighting (devon's approach)

  • Houdini modify to export 3 lighting channels + density
  • Modify shader to take channel ramps into account
  • Make pretty visuals

  • Implement

  • IsoSurface Tracking
    • Mean Occlusion
    • Directional Occlusion
    • Directional Lightfield
  • Re-export Volume Flipbook sample
  • Reference pathtrace/raymarch
  • Particle Rendering with Slabs sampling
  • Basis Functions

    • Create DbgVisualizer for Lightfield at volume isosurface
    • Visualize Light Along Ray
    • Visualize Final Light out
    • Visualize Incoming Light
    • Project that onto basis functions
    • Grid Basis
    • Spherical Harmonics
    • Spherical Gaussians
    • HBasis
    • NiceToHave Incorporate Baked VLM#

    • VolumetricFog.usf: LightScatteringCS() - GetVolumetricLightmapSH2(BrickTextureUVs);
  • Basic Scaffolding

  • Make a simple houdini -> ue4 plugin then iterate.

  • Houdini:

  • create voxel grid
  • create attribs (bakedirect,scatter,env)
  • Make a nice volumetric mesh
  • Sample based on plane alignment
  • bake direct into samples
  • bake scattering into samples
  • bake indirect into samples
  • export
    • render volume texture
    • Sample cop into texture as channel lighting
    • render fbx of isosurface
  • Bake thickness

    • Bake to SH
  • UE4:

  • import voltex
  • import mesh
  • write raymarch shader
    • raymarch lightcontrib
    • colorramp for direct/indirect
  • Temporal Reprojection
  • Perf
    • Optimize existing shader
    • LOD
    • Bake to IsoSurface
    • LOD Mips
    • Perf analysis
  • Monkey Engineering/Production grade

    • Support exporting to tangents basis
    • Support for skinned meshes
    • Remove 'houdinispace' swizzle and properly export out of houdini
  • Debugging

  • VLM UE4 Debug
    • Peek Texel
  • Basis Func UE4 Debug Visualization

    • Peak basis function
  • NiceToHave#

  • make a UE4 HDA
  • incorporate UE4 VLM
  • PRT Compression: Manny Ko - Practical Spherical Harmonics Based PRT Methods
  • Sloan - Efficient Spherical Harmonic Evaluation
  • Noise-Resistant Fitting for Spherical Harmonics
  • NiceToHave Volume Filtering with mips#

  • NiceToHave Linear Regression on Basis Function#

  • NiceToHave Instant Neural Graphics Primitives with a Multiresolution Hash Encoding#

  • NiceToHave SMERF: Streamable Memory Efficient Radiance Fields for Real-Time Large-Scene Exploration#

Research Snippets#

Channel Lighting Magic#

  • Devon Penney's overview of his technique from Allumette: DigiPro '16 - Volumetric clouds in the VR movie, Allumette

    Right now the rays terminate with the max samples per ray, which is ~25, and in general the rays early terminate with a density close to 1. This works for my clouds because they are so dense, and most rays early terminate except for gazing angles.

    Try to do some experiments with straight ray marching, just for comparison. In my tests, I got nicely convergent renders with a 970 + Vive @ ~1.2ms GPU time, and some overhead for rendering the cloud shell into custom depth (.3-.4ms). There isn't much CPU overhead. This is with 25 samples per ray and my dense clouds with a 3d texture that is 950x950x600

    So yes, I did bake in 3 lights and denisty into the grid as a preprocess in Houdini

    in Houdini, I did a whole bunch of volume renders from different angles, and configured it to output ray march points where each point was the attenuated light that reached that point in space.

    it was a massive amount of data that was then resampled to a vdb grid, then output to a custom format rgba

    im not totally sure what your dLo and ds are, but the basic idea is to remap the rgb you get at each step, then attenuate that by the transmittance. While this talk is more based on analytical methods, I like the description for the math:

    the remap I used was very simple - I just did:
    VolumeRadianceAtSample = VolumeSample.r * KeyLightColor + VolumeSample.g * MultipleScatteringColor + VolumeSample.b * EnvironmentLightColor

    and yes, I did apply this at each ray march step rather than at the end. It'll look a bit better and be more flexible, but in theory, you can remap at the end too (we did that at DreamWorks all the time so you could remap colors in compositing)

    the key to getting it look good is baking in really solid lighting and using a reasonably high resolution grid

    and I had a really good lighting artist tweak the lighting channel remapping a lot 🙂

    I could try to dig up the math I used too if you get stuck on the numerical integratio

Math Reminders#

  • Incremental averaging
  • NewAvg = OldAvg + (NewVal - OldAvg) / NewSampleCount
  • Optimized: Avg = lerp(avg, NewVal, rcp(NewSampleCount))
  • For calculating variance as well:'s_online_algorithm

  • Closest Point Transform

  • ∇_sdf() is always unit vector. (SDF is 3D levleset of function embedded in 4D so all level set rules apply)
  • Xcpt(x) = x - sdf(x) * ∇_sdf(x)
  • Xcpt(x) => is a conservative field
    • Xcpt(x) = ∇U(x)
    • U(x) = 0.5 * (|x|^2 - f^2(x))
    • Has no curl

Optimization Reminders#

Curve Fitting#

  • Fast Polynomial Eval
  • Horner form for fast polynomial evaluation:
    y = x + a*x*x*x + b*x*x*x*x*x + c*x*x*x*x*x*x*x + d*x*x*x*x*x*x*x*x*x*;* // 24 mults, 4 adds
    z = x*x; y = ((((z*d+c)*z+b)*z+a)*z+1)*x; // 2 mults, 4 madds

  • Error metrics

  • Absolute error metric: error_abs = abs(f_actual - f_approx)
    • good measure of accuracy but not of importance of any error
    • Ex: Error of 3 is fine if f(x) returns 38,000. Terrible if function returns 0.0001
  • Relative error metric: 1 - f_approx / f_abs

  • Gaussian Quadrature

  • Spherical Splines/Polynomials

  • Spherical RBFs

  • Is There Anything Comparable to Spherical Harmonics But Simpler?
  • Von Mises Basis Functions vs Gaussian Spherical Radial Basis Functions:
    • A Comparison of the von Mises and Gaussian Basis Functions for Approximating Spherical Acoustic Scatter
    • 3 orders of magnitude better than guassian
  • Real-time Rendering of Dynamic Scenes under All-frequency Lighting using Integral Spherical Gaussian

Future Research#

Promising Future Directions#

Misc Thoughts#