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Realtime Caustics using Distributed Photon Mapping

Realtime Caustics using Distributed Photon Mapping. Johannes Günther Ingo Wald * Philipp Slusallek Computer Graphics Group Saarland University ( * now at MPII Saarbrücken). Introduction. What is wrong with this picture?. Introduction. With caustic illumination. Outline.

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Realtime Caustics using Distributed Photon Mapping

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  1. Realtime CausticsusingDistributed Photon Mapping Johannes Günther Ingo Wald* Philipp Slusallek Computer Graphics Group Saarland University (*now at MPII Saarbrücken)

  2. Introduction • What is wrong with this picture? EGSR 2004, Norrköping, Sweden

  3. Introduction • With caustic illumination EGSR 2004, Norrköping, Sweden

  4. Outline • Introduction & Motivation • Previous Work • Analysis of Photon Mapping • Faster Photon Mapping • Parallelization Issues • Results & Examples EGSR 2004, Norrköping, Sweden

  5. Previous WorkCaustics • (Bidirectional) path tracing [Lafortune, Veach] • Need many samples  too slow / too noisy • Density estimation [Shirley, Walter] • Use of pre-computed, view-independent illumination representation  Not interactive • Particles in hierarchical radiosity system [Granier] • Particle tracing accelerated by exploiting HR structure • Still too slow for interactive use • Hardware based projection [Wand] • Implemented via texture lookups on GFX • Limited to far lights and no occluders considered • Only reflective caustic generators EGSR 2004, Norrköping, Sweden

  6. Previous Work Photon Mapping • Photon map [Jensen] • Preferred tool for caustics • Independent of scene geometry • But problematic for interactive use (later) • Hashed photon mapping [Wald] • Approximation  lower quality • On programmable graphics hardware [Purcell] • Also approximative • Limited performance (interactive only at low resolution) • No caustics during interaction • Simple scenes EGSR 2004, Norrköping, Sweden

  7. Outline • Introduction & Motivation • Previous Work • Analysis of Photon Mapping • Faster Photon Mapping • Parallelization Issues • Results & Examples EGSR 2004, Norrköping, Sweden

  8. Analysis – Overview Photon Map: • Preprocessing • Photon generation • Construction of kd-tree • Queries during rendering • Search k-nearest photons  Density estimation EGSR 2004, Norrköping, Sweden

  9. Analysis • Interactivity: now ‘pre’processing every frame • High quality caustic: > 100K photons • No problem with realtime ray tracing (>4Mrays/s)? • Low caustic photon yield • Several rays per photon • Only few photons contribute to caustics(in many cases below 10%) • Slow photon shooting • Incoherent rays  slow ray tracing, no SSE • Costly light source and BRDF sampling(up to 60% of total shooting time)  4-15 times slower EGSR 2004, Norrköping, Sweden

  10. Analysis • Building kd-tree • Serious problem with many photonscomplexity O(n log n) • Hard to parallelize • Small changes in map  complete rebuild • Queries are costly • Traversal of kd-tree • Density estimation  About 10 times as expensive as tracing a ray  Have to address all of these problems EGSR 2004, Norrköping, Sweden

  11. Outline • Introduction & Motivation • Previous Work • Analysis of Photon Mapping • Faster Photon Mapping • Parallelization Issues • Results & Examples EGSR 2004, Norrköping, Sweden

  12. Selective Photon Tracing [Dmitriev] • Adaptive sampling in path space • Exploiting similarity property of Halton numbers • Indirect caustics captured • Improve yield by factor 4 EGSR 2004, Norrköping, Sweden

  13. Improve kd-tree • Balancing kd-tree requires costly median finding • Instead: “split in middle” • Spatial center of current voxel • Now unbalanced  Construction 1.5-4 times faster EGSR 2004, Norrköping, Sweden

  14. Improve kd-tree • Balancing kd-tree requires costly median finding • Instead: “split in middle” • Spatial center of current voxel • Now unbalanced  Construction 1.5-4 times faster • Not intuitive: also traversal faster [Wald ’04] • Better adaptation to photon density  Query 1.5-2.5 times faster EGSR 2004, Norrköping, Sweden

  15. Accumulation of Photons • Performance still not enough for high quality  Improve quality by accumulation across frames • kd-tree with “split in middle” allows augmentation • Accumulated result is view-independent!  High quality walkthrough EGSR 2004, Norrköping, Sweden

  16. Outline • Introduction & Motivation • Previous Work • Analysis of Photon Mapping • Faster Photon Mapping • Parallelization Issues • Results & Examples EGSR 2004, Norrköping, Sweden

  17. 27k photons 5x5 interleaving filtered Interleaved Sampling & Filtering [Keller] • Quality comparable to 25 x 27k = 680k photons EGSR 2004, Norrköping, Sweden

  18. FilteringCaustic Illumination • Originally: restrict filtering to smooth regions • Continuity tests on server limits to 5fps (IGI [Wald ’02]) But: • Only filter caustic illumination • Potential artifacts less visible  No need for costly discontinuity checks New: • Simple box filter  efficient implementation • SSE, cache friendly, independent of filter size • Performance: CPU 300 fps, network now ~22 fps EGSR 2004, Norrköping, Sweden

  19. Outline • Introduction & Motivation • Previous Work • Analysis of Photon Mapping • Faster Photon Mapping • Parallelization Issues • Results & Examples EGSR 2004, Norrköping, Sweden

  20. Performance • Scalability: roughly linear • Upper limit: about 22 fps (network bounded) EGSR 2004, Norrköping, Sweden

  21. Comparison to IGI [Wald ’02] • Same #clients (9) and frame rate (4.8 fps) new system IGI system 2600 phs 8000 phs 2500 phs 16000 phs EGSR 2004, Norrköping, Sweden

  22. Examples • Indirect caustics • No performance drop EGSR 2004, Norrköping, Sweden

  23. Examples • Headlight simulation • Complex model • Many layers of glass • Pointlights inside bulbs • Using 18 Dual clients 250k phs / 3 fps 25M phs / 11 fps EGSR 2004, Norrköping, Sweden

  24. Examples • Headlight simulation • Complex model • Many layers of glass • Pointlights inside bulbs • Using 18 Dual clients 250k phs / 3 fps 25M phs / 11 fps photo EGSR 2004, Norrköping, Sweden

  25. Video EGSR 2004, Norrköping, Sweden

  26. Conclusion • Improvements on all aspects of the photon map • Improved yield by Selective Photon Tracing • Optimized kd-tree (construction and traversal) • Efficient parallelization • Interleaved Sampling • Faster filtering  Realtime caustic simulation  High quality walkthrough  Linear scalability, up to 22 fps EGSR 2004, Norrköping, Sweden

  27. Questions ? Questions ? EGSR 2004, Norrköping, Sweden

  28. EGSR 2004, Norrköping, Sweden

  29. 5x5 filter, blurring over edges hardly visible No discontinuity buffer? EGSR 2004, Norrköping, Sweden

  30. EGSR 2004, Norrköping, Sweden

  31. Photon Map Two pass approach: • Preprocessing • Generation • Emit photons into scene • Trace path until absorption • Construction of kd-tree • For fast retrieval of hit points • During rendering (ray tracing) • At each point to shade: do query • Search k-nearest photons • Accumulate power & divide by occupied area • Density estimation Concentrate on caustics EGSR 2004, Norrköping, Sweden

  32. Client-Server Approach • High computational cost  need parallelization • even more necessary with photon mapping • Commodity PCs • 24 Dual-AthlonMP 1800+ • For ray tracing • “Thin” clients: 100 Mbit Ethernet, no graphics card, ... • 1 server node • Runs application, controls clients, etc. • Fully switched 100MBit network • Gigabit uplink to server EGSR 2004, Norrköping, Sweden

  33. Outlook • Combination with Instant Radiosity / IGI2 to add indirect illumination • Further improve sampling and caustic photon yield • Still need a cluster  Special Hardware (e.g. SaarCOR) EGSR 2004, Norrköping, Sweden

  34. Goal • Generate and visualize caustic light effects • Interactive frame rates • At video resolution 640x480 • Support complex scenes • Preview quality acceptable during scene modifications • High quality walkthroughs EGSR 2004, Norrköping, Sweden

  35. Improve Yieldof Caustic Photons • Cannot help on #rays per photon path • But: improve efficiency of sampling • Jensen: • Project caustic generators onto (hemisphere of) light sources, sample only occupied solid angle • Captures only direct caustics • Mesh dependent, not in realtime • Wald: • Project only bounding volume • Geometry independent • Bounding volume often too coarse approximation • Requires manual user interaction / scene preparation EGSR 2004, Norrköping, Sweden

  36. Distribution Options • Generate same photon map on each client • Inefficient, only rendering/queries in parallel • Not scalable • Generate different parts of photon map on clients • Need exchange of photons • But: network bandwidth too small • Rendering can only start after receiving all photons latency • Generate different photon maps on clients • Combine illumination on server by interleaving pixels • Reduce noise by filtering in image space  Interleaved sampling & discontinuity buffering [Keller] EGSR 2004, Norrköping, Sweden

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