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A Layered Depth-of-Field Method for Solving Partial Occlusion

A Layered Depth-of-Field Method for Solving Partial Occlusion. David C. Schedl Michael Wimmer schedl@cg.tuwien.ac.at wimmer@cg.tuwien.ac.at Institute of Computer Graphics and Algorithms Vienna University of Technology. WSCG – 26 th June 2012. Real life partial occlusion.

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A Layered Depth-of-Field Method for Solving Partial Occlusion

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  1. A Layered Depth-of-Field Method for Solving Partial Occlusion David C. Schedl Michael Wimmer schedl@cg.tuwien.ac.atwimmer@cg.tuwien.ac.at Institute of Computer Graphics and Algorithms Vienna University of Technology WSCG – 26th June 2012

  2. Real life partial occlusion f=18 mm, N=4 David C. Schedl

  3. Intro/Overview • depth-of-field approximation • post processing • partial occlusion in realtime David C. Schedl

  4. Thin lens David C. Schedl

  5. Previous work • Potmesil and Chakravarty, 1981 • CoC - equation • first post-processing method • blur according to CoCs • still a reference • artifacts David C. Schedl

  6. Artifacts • color bleeding: • depth discontinuity: [Riguer2005] [Demers2004] David C. Schedl

  7. Partial Occlusion • pinhole vs. finite aperture David C. Schedl

  8. Partial Occlusion • pinhole: • finiteaperture: David C. Schedl

  9. Previous work – solve partial occlusion • non-realtime: • ray-tracing (Cook et al., 1984) • Accumulation B. (Haeberli and Akeley, 1990) • layered methods: • Kraus and Strengert, 2007 • occluded scene content only interpolated • Lee et al., 2010 • image composition via ray traversal • simulate more lens effects • more complex and slower than ours David C. Schedl

  10. Our Method David C. Schedl

  11. Our Method David C. Schedl

  12. Overview David C. Schedl

  13. & Depth Peeling Rendering Images David C. Schedl

  14. Matting – functions weight depth David C. Schedl

  15. Matting – functions weight depth David C. Schedl

  16. Matting – layers Input David C. Schedl

  17. Matting – layers Input David C. Schedl

  18. Matting – layers Input Layers David C. Schedl

  19. Matting – layers Input Layers David C. Schedl

  20. Matting – layers Input Layers David C. Schedl

  21. Blurring • uniformly blur layers • Gaussian filter David C. Schedl

  22. Blurring David C. Schedl

  23. Blurring David C. Schedl

  24. Compose • alpha-blendback to front David C. Schedl

  25. Optimization • reduce filter width • recursive Gaussians David C. Schedl

  26. Optimization - front David C. Schedl

  27. Optimization - front David C. Schedl

  28. Optimization - front David C. Schedl

  29. Optimization - Compositing David C. Schedl

  30. Results - Homunculus f=100mm, N =1.4, focus=18 500 mm, 17 layers, 3x DP David C. Schedl

  31. Results - Dragons f=100mm, N =1.4, focus=3 000 mm, 22 layers, 3x DP David C. Schedl

  32. Results – Benchmarks • Intel Core i7 920, Geforce GTX 480 • OpenGL and GLSL • 1024 x 1024px David C. Schedl

  33. Conclusion • layered DoF method • partial occlusion solved • comparison to: • Accumulation Buffer • Lee et al., 2010 • optimized by recursive Gaussians • efficient composition with alpha blending David C. Schedl

  34. Outlook • screen-spaced antialiasing • avoid empty layers: clustering • inaccurate but faster blurring methods • combine with eye-tracker David C. Schedl

  35. Thank you! slides will be available at: http://www.cg.tuwien.ac.at/research/publications/2012/schedl-2012-dof/ David C. Schedl

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