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Soft Shadow Volumes for Ray Tracing

Soft Shadow Volumes for Ray Tracing. Samuli Laine Helsinki University of Technology, Hybrid Graphics Ltd. Timo Aila Helsinki University of Technology, Hybrid Graphics Ltd. Ulf Assarsson ARTIS, GRAVIR /IMAG INRIA, Chalmers University of Technology. Jaakko Lehtinen

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Soft Shadow Volumes for Ray Tracing

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  1. Soft Shadow Volumes for Ray Tracing Samuli Laine Helsinki University of Technology, Hybrid Graphics Ltd. Timo Aila Helsinki University of Technology, Hybrid Graphics Ltd. Ulf Assarsson ARTIS, GRAVIR /IMAG INRIA, Chalmers University of Technology Jaakko Lehtinen Helsinki University of Technology, Remedy Entertainment Ltd. Tomas Akenine-Möller Lund University

  2. We present An algorithm for computing Soft Shadows • For planar area light sources • Exactly the same shadows as using shadow rays • Faster - up to 2 orders of magnitude • Can compute very high resolution soft shadows with low extra cost • E.g. allows for 1000 shadow samples per pixel • Requires computation of silhouettes • Trivial for polygon-based scenes

  3. Soft Shadows – A Quick Recap • Area lights give soft shadows Point light Area light Hard shadow Soft shadow

  4. pixel Classic solution • Multiple shadow rays Lots of shadow rays per pixel

  5. Our solution - overview • Replace the shadow rays • With soft shadow volume computations • Plus one reference shadow ray One shadow ray + soft shadow volume computations Lots of shadow rays per pixel pixel pixel Classic approach Our approach

  6. What’s a Soft Shadow Volume? Light source Soft Shadow Volume = A. Volume from which an edge projects onto the light source B. Region of penumbra caused by an edge Shadow caster Soft Shadow Volume

  7. Our solution - overview Two parts: • from any receiving point p, we need to find silhouette edges affecting the visibility • A method for computing the visibility from silhouette information

  8. Finding potential silhouettes Fast method for determining silhouette edges that overlap light source from p Arbitrary shadow caster Arbitrary shadow receiving point p HOW?

  9. hemicube Bottom face of hemicube p This cell contains potential silhouette edges from p Hemicube Construction Rasterize soft shadow volumes into a hemicube for each light source Each cell contains list of edges Each cell contains list of edges

  10. Bottom face of hemicube Hemicube Construction Wedge marked to all cells it even partially overlaps → no artifacts Rasterize soft shadow volumes into a hemicube for each light source Each cell contains list of edges

  11. Bottom face of hemicube Hemicube Construction Wedge marked to all cells it even partially overlaps → no artifacts Each cell contains list of edges

  12. Hemicube Construction Lots of edges does not need to be considered

  13. p1 p2 Hemicube Construction Lots of edges does not need to be considered Because these edges cannot be silhouettes projected onto the light source from any point p

  14. Wedge Creation Criterions • Wedges are created for all edges that are silhouettes from any point on the light source • The wedge includes all positions from which the edge projects onto (occludes) the light source.

  15. p p During Rendering • Hemicube returns a conservative set of edges • All the necessary edges but also many more • We only want edges that are • Silhouettes from p • Project onto the light source. • Tested with Point-inside-wedge • Now we have the silhouette edges from p

  16. Visibility Reconstruction • Which light samples si are visible from point p? • Brute force: cast a shadow ray for each si • Our recipe: 1. Find silhouette edges between p and light source 2. Project them onto light source  reduces to 2D 3. Compute relative depth complexity for every si 4. Solve visibility with a single shadow ray 5. Profit

  17. 0 1 1 0 2 1 1 Depth Complexity • Depth complexity of si = number of surfaces between p and si  0 Light source as seen from p Depth complexity function

  18. 0 1 1 0 2  1 1 From Silhouette Edges to Relative Depth Complexity • Projected silhouette edges define the first derivative of the depth complexity function • Hence, relative depth complexity can be solved by integrating the silhouette edges over the light source • Integration islinear  can beperformed oneedge at a time

  19. 1 +1 1 -1 1 -1 Integration: Example • Left-to-right integration of a triangular silhouette 0  0 Light source as seen from p Depth complexity function

  20. +1 Integration: Sampling Points • We don’t need the value of the depth complexity function except at the sampling points si • Sufficient to maintain a depth complexity counter for each si • Integration: find si that are insideupdate region and update theirdepth complexity counters

  21. Integration: Rules • There’s a caveat - we only have the edges that overlap the light source • Loops are not necessarily closed, since parts outside the light source may be missing We don’t have this edge!

  22. Integration: Rules • Solution: apply special rules to edges that cross the left side of the light source • This accountsfor potentiallymissing edges

  23. Integration: Optimization • Place the light samples into uniformly sized buckets • During integration, only process affected buckets • Most edges span only one bucket • We use approx. sqrt(N)buckets for N light samples • We also process 4 samplesin parallel using SSE vectorinstructions

  24. From Relative Depth Complexity to Visibility • We are not done yet, since the constant of integration is not known  cannot solve visibility • Solution: cast a shadow rayray to one si with lowestrelative depth complexity • If blocked, all si are blocked • Otherwise, all si with lowest rel.depth complexity are visible

  25. Experimental Results • Comparisons done using a commercial ray tracer • Turtle by Illuminate Labs • Enabled heuristic shadow ray casting: stop if first 50% of rays agree • Our method was implemented into this ray tracer • We use the same ray caster for casting the reference ray

  26. Columns: 580 triangles, adaptive AA, 960x540

  27. Formula: 60K triangles, adaptive AA, 960x540

  28. Sponza: 109K triangles, adaptive AA, 960x540

  29. Robots: 1.3M triangles, adaptive AA, 960x540

  30. Ring: 374K triangles, adaptive AA, 960x540

  31. Conclusions • Fast shadow algorithm in wide range of scenes • Easy to plug into an existing ray tracer • Scalability considerations • Number of light samples: excellent (~ sqrt M) • Number of triangles: good (silhouettes: ~ N(something ≤ 1)) • Output resolution: not so good (linear) • Spatial size of the light source: not so good (~ linear)

  32. Future Work • GPU implementation? • Improvement of the acceleration structure • To pump up the edge acceptance ratio (currently < 10%)

  33. Thanks • Questions Thanks for the cash: Bitboys, Hybrid Graphics, Remedy Entertainment, Nokia, National Technology Agency of Finland, ATI, Illuminate Labs, French Ministry of Research, Chalmers, Hans Werthén foundation, Carl Tryggers foundation, Ernhold Lundströms foundation, Swedish Foundation for Strategic Research

  34. Semi-transparent shadow casters • Detect the light samples that are occluded only by semi-transparent occluders • Determine the color for these light samples by casting shadow rays Blocked ??? Blocked Visible

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