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Free Path Sampling in High Resolution Inhomogeneous Participating Media

Free Path Sampling in High Resolution Inhomogeneous Participating Media. Szirmay-Kalos László Magdics Milán Tóth Balázs. Budapest University of Technology and Economics, Hungary. Problem statement. GI rendering in participating media: Free path between scattering points

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Free Path Sampling in High Resolution Inhomogeneous Participating Media

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  1. Free Path Sampling in High Resolution Inhomogeneous Participating Media Szirmay-Kalos László Magdics Milán Tóth Balázs BudapestUniversity of Technology and Economics, Hungary

  2. Problem statement • GI rendering in participating media: • Free path between scattering points • Absorption or scattering • Scattering direction

  3. Free Path Sampling CDF of free path r s Optical depth Sampling equation

  4. Homogeneouscase is simple r s

  5. Ray marching • Complexity grows with the resolution • Independent of the density variation • Slow in high resolution low density media Reject Reject Accept

  6. Woodcock tracking Acceptwith prob: (t)/max • Resolution independent • Complexity grows with the density variation • Slow in strongly inhomogeneous media

  7. Contribution of this paper • Sampling scheme for inhomogeneous media • Generalization of Woodcock tracking and ray marching • Involves them as two extreme cases • Offers new possibilities between them • Application for high resolution voxel arrays • Application for procedurally generated media of ”unlimited resolution”

  8. Inhomogeneousmedia Scattering lobe (albedo + Phase function) variation Spatial density variation Free path Photon Particle and its scattering lobe Collision High density region In free path sampling only density variation matters! Low density region

  9. Mix virtual particles to modify the density but to keep the radiance Virtual collision Virtual particle and its scattering lobe Photon Real collision Probability of hitting a real particle: (t)/((t)+virtual (t))=(t)/comb(t)

  10. Sampling with virtual particles • Find comb(t) = (t)+virtual(t) • upper bounding function extinction comb(t), • Analytic evaluation: • Sample with comb(t) • Real collision with probability (t)/comb(t)

  11. Challenges • For the volume density find an analytically integrable sharp upperbound • Voxel arrays: constant or linear upper-bound in super-voxels • Procedural definition: depends on the actual procedure • We demonstrate it with Perlin noise

  12. Procedural media (Perlin noise)

  13. Upper bound: construction up to a limited scale upper-bound noise original resolution super-voxel resolution

  14. Line integration scattering point where super-voxels ray optical depth real depth original voxels

  15. 5123voxel array, 32 million rays Ray marching: 9 sec: Woodcock: 7 sec: New: 1.4 sec: Million rays per second with respect to the super voxel resolution

  16. Perlin noise clouds, 9 million rays

  17. Scalability Million rays per second

  18. Videos • 40963 effective resolution • 1283 super-voxel grid • 50 million photons/frame • 9 sec/frame • 40963 effective resolution • 1283 super-voxel grid • 5 million photons/frame • 1 sec/frame

  19. Conclusions • Handling of inhomogeneous media by mixing virtual particles that • Simplify free path length sampling • Do not change the radiance • Compromise between ray marching and Woodcock tracking • Much better than ray marching in high resolution media • Much better than Woodcock tracking in strongly inhomogeneous media

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