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LIGHT TRANSPORT 25/11/2011 Shinji Ogaki. 4 Papers Progressive Photon Beams Lightslice: Matrix Slice Sampling for Many- Lights Problem Modular Radiance.

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Presentation on theme: "LIGHT TRANSPORT 25/11/2011 Shinji Ogaki. 4 Papers Progressive Photon Beams Lightslice: Matrix Slice Sampling for Many- Lights Problem Modular Radiance."— Presentation transcript:

1 LIGHT TRANSPORT 25/11/2011 Shinji Ogaki

2 4 Papers Progressive Photon Beams Lightslice: Matrix Slice Sampling for Many- Lights Problem Modular Radiance Transfer Practical Filtering for Efficient Ray-Traced Directional Occlusion

3 PROGRESSIVE PHOTON BEAMS Wojciech Jarosz et at.

4 1.Cast Photons 2.Gather Photon Mapping Photon Query Point Fixed Search Radius

5 LS+DS+E Paths Accurate Caustics Unlimited # of Photons Progressive Photon Mapping Photon Reverse Photon Search Radius

6 Extension to Volume (LS+MS+E Paths) PPB (Progressive Photon Beam) Photon Beam Query Ray

7 L: Radiance Tr: Transmittance s: Surface m: Media σs: Scattering Coefficient f: Phase Function Radiative Transport Equation Photon Beam Query Ray Xs S Xw W

8 Beam x Beam 1D Estimator FluxKernel Scattering Coef

9 Results

10 LIGHTSLICE: MATRIX SLICE SAMPLING FOR MANY-LIGHTS PROBLEM Jiawei Ou et al.

11 Many-Lights Problem Global Illumination (Diffuse Indirect Illum.) Matrix Interpretation of Many-Lights VPL (Virtual Point Light)

12 Many-Lights Problem Global Illumination (Diffuse Indirect Illum.) Matrix Interpretation of Many-Lights VPL (Virtual Point Light)

13 Many-Lights Problem Global Illumination (Diffuse Indirect Illum.) Matrix Interpretation of Many-Lights VPL (Virtual Point Light)

14 Many-Lights Problem Global Illumination (Diffuse Indirect Illum.) Matrix Interpretation of Many-Lights VPL (Virtual Point Light)

15 Many-Lights Problem Global Illumination (Diffuse Indirect Illum.) Matrix Interpretation of Many-Lights VPL (Virtual Point Light)

16 Many-Lights Problem Global Illumination (Diffuse Indirect Illum.) Matrix Interpretation of Many-Lights VPL (Virtual Point Light)Sample

17 Transport Matrix Close to Low Rank..

18 Algorithm 1.Matrix Slicing 2.Slice Sampling 3.Initial Light Clustering 4.Per Cluster Refinement

19 Results SliceVisualization

20 Results (cont’d) Lightslice MRCS Lightcut

21 Limitations Parameter Selection (# of Slices etc.) Glossy Surface Animation Matrix Sparsity Comprehensive Comparison is missing (Coherent Light Cut and Pixelcuts?)

22 MODULAR RADIANCE TRANSFER Bradford J. Loos et al.

23 Module Patched Local is Global Module

24 Shapes

25 Transport Matrix (Local) F: Direct to Indirect Transfer (One Bounce) Sample

26 Reduced Direct-to-Indirect Transfer in Shape Truncated SVD of F Not so Sparse, Unfortunately Sample

27 Reduced Direct-to-Indirect Transfer in Shape (cont’d) Light Prior (Basis for Plausible Direct Lighting) Id1Id2Idm……

28 Reduced Direct-to-Indirect Transfer in Shape (cont’d) Truncated SVD of M Very Sparse Sample

29 Reduced Direct-to-Indirect Transfer between Shapes (Local to Global) Interface

30 Results

31 Limitations Lighting Condition outside of the Light Prior High Frequency Glossy Transport Large Scale Indirect Shadows within Blocks Dictionary Shapes (e.g. Internal Occluders) User Interface

32 PRACTICAL FILTERING FOR EFFICIENT RAY-TRACED DIRECTIONAL OCCLUSION Kevin Egan et al.

33 Ambient Occlusion ( )/5=0.6 Hemisphere

34 1.Cast Rays 2.Filter Ambient Occlusion with a Sparse Set of Rays Expensive Cheap

35 Distant Lighting in Linear Sub-Domains

36 Frequency Analysis and Sheared Filtering Light(y) Receiver(x) x y Occluder Spectrum Bandlimited by Filter Flatland Scene Occlusion Function f(x, y) 0 Receiver(x) 1 0 Light(y) 1 x y Occluders x y

37 Frequency Analysis and Sheared Filtering (cont’d)

38 Rotationally-Invariant Filter Infinitesimal Sub-domains

39 Results 6+ mins to filter 

40 Limitations Artifacts due to Undersampling in the 1st Pass Smoothes out some Areas of Detail Noise in Areas where Brute Force Computation is used


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