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Efficient Rendering of Local Subsurface Scattering Tom Mertens 1, Jan Kautz 2, Philippe Bekaert 1, Frank Van Reeth 1, Hans-Peter Seidel 2 1 2.

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Presentation on theme: "Efficient Rendering of Local Subsurface Scattering Tom Mertens 1, Jan Kautz 2, Philippe Bekaert 1, Frank Van Reeth 1, Hans-Peter Seidel 2 1 2."— Presentation transcript:

1 Efficient Rendering of Local Subsurface Scattering Tom Mertens 1, Jan Kautz 2, Philippe Bekaert 1, Frank Van Reeth 1, Hans-Peter Seidel 2 1 2

2 Overview Problem Related Work Local Subsurface Scattering Our Approach Implementation & Results Discussion Summary & Future Work

3 Subsurface Scattering BRDFBSSRDF opaque translucent

4 BSSRDF model function of distance introduced by Jensen et al. (SIGGRAPH’01) multiple scattering materials with high albedo: marble, milk, wax, skin,…

5 BSSRDF model function of distance introduced by Jensen et al. (SIGGRAPH’01) multiple scattering materials with high albedo: marble, milk, wax, skin,…

6 Related Work Jensen et al. ’02 –General scattering effects –Offline rendering Mertens et al. ’03 –Dynamic models –General scattering effects –Per vertex Our paper –Dynamic models –Local scattering effects –Per pixel

7 Local Subsurface Scattering Certain cases no global response –Dense materials –Large scale Distinct appearance! –Rough surface Local sampling sufficient But accuracy is important! –R d decays exponentially –Per vertex too coarse Apply to skin rendering Only local response Global response

8 Local Subsurface Scattering Local subsurface scattering Diffuse

9 Local Subsurface Scattering Local Full

10 Our Approach High level description –Employ importance sampling scheme for R d –Rendering algorithm Generate importance samples Render irradiance image Integrate irradiance image locally in tangent plane

11 Importance Sampling of R d Need to solve integral Idea: sample according to R d  Result: set of distances r i Issues: –Need samples on surface, not r i ’s –Need irradiance at sample

12 Importance sampling of R d Solution: –Pick a view e –Render irradiance to image T –Generate sample p’ in tangent plane –Project p’ on surface  p –Project p’ into T to retrieve irradiance E(p’)

13 Importance sampling of R d We take eye position for e p’  p implies a jacobian J –ratio of solid angles Integral becomes:

14 Rendering Algorithm Generate importance samples in 2D 2D RdRd riri

15 Rendering Algorithm Render irradiance image

16 Rendering Algorithm Integrate image locally in tangent plane

17 Rendering Algorithm Store result in final image

18 Implementation Variance reduction –Stratified sampling Deterministic, pseudo random –Interleaved sampling Noise  dither pattern –Combined sampling Importance + uniform Irradiance discontinuties Software implementation Programmable Graphics Hardware Combined sampling Uniform importance

19 Implementation Programmable Graphics Hardware –Overview: generate 2D samples –quick per-frame preprocess in software Render irradiance image T Bind E as texture For each sample –Look up sample E in T (pixel shader) –Accumulate E in temporary texture Output temporary texture

20 Results ATI Radeon 9700 Pro 500x500 image, 4 to 5 frames/sec Some pictures…

21 Image Quality Color bleeding (forehead)Shadow smoothing

22 Image Quality nVIDIA’s skin shaderOur method

23 Complex lighting

24 Demo video

25

26 Discussion No global effects –E.g. backlit ears Prone to noise –Irradiance discontinuities Shadow borders –Geometric discontinuities Kills effect of importance sampling Ghosting artifacts Accumulation  fill-rate limited ghosting

27 Summary Novel technique for local subsurface scattering Amenable for hardware implementation Interactive frame rates Dynamic models Application: skin rendering

28 Future Work Hybrid algorithm –Global response per vertex –Local response per pixel Eliminate ghosting –Apply technique in texture space Combine with skin BRDF Take into account varying blood concentrations

29 Acknowledgments Head model courtesy of nVIDIA Funding: European Regional Development Fund


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