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Real-Time, All-Frequency Shadows in Dynamic Scenes

Some materials are get from the author and this paper is presented by CG, Huang. Real-Time, All-Frequency Shadows in Dynamic Scenes. Outline. Introduction Relate work Convolution Generation of Area Lights for Environment Maps Limitations Result. Outline. Introduction Relate work

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Real-Time, All-Frequency Shadows in Dynamic Scenes

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  1. Some materials are get from the author and this paper is presented by CG, Huang Real-Time, All-Frequency Shadows in Dynamic Scenes

  2. Outline • Introduction • Relate work • Convolution • Generation of Area Lights for Environment Maps • Limitations • Result

  3. Outline • Introduction • Relate work • Convolution • Generation of Area Lights for Environment Maps • Limitations • Result

  4. Introduction • Enable real-time, all-frequency shadows in dynamic scenes. • Support area light as well as wnviroment lighting. • The key contribution is renderng plausible soft shadow. • Enviroment-lit scenes can be rendered.

  5. Outline • Introduction • Relate work • Convolution • Generation of Area Lights for Environment Maps • Limitations • Result Soft Shadows Convolution Precomputation and Simplification Environment map sampling

  6. Soft shadows • Early work on shadow mapping extensions image-based rendering to average hard shadow.[Chen and Williams 93; Agrawala et al. 00] • Classic shadow volumn method was extended to soft shadows.[Assarsson and Akenine-Moller 03]

  7. Convolution • Soler and Sillion[98] propose an image-based shadow algorithm based on convolution. • Don’t support self-shadowing. • Variance shadow maps[Donnelly and Lauritzen 06] • Convolution shadow maps[Annen et al. 07]

  8. Precomputation and simplification • PRT [Sloan et al. 02] calculate and stroes an illumination-invariant transport solution off-line and uses it for real-time relighting. • Challenging to support fully dynamic scenes with arbitrary illumination.

  9. Environment map sampling • Agarwal et al.[03] proposed an efficient point sampling strategy for environment maps. • Arbree et al. Use disk-shaped light sources to approximation. • This paper approximate an environment with a collection of square light sources.

  10. Outline • Introduction • Relate work • Convolution • Generation of Area Lights for Environment Maps • Limitations • Result

  11. L p z(p) c d(x) x Convolution shadow map • xR3 • pR2 • P = T(x) • Shadow function:s(x):=f(d(x),z(p)) • Binary result: • 1 if d(x)<=z(p) • 0 else

  12. L p d(x’) z(p) c x x’ Shadow test function: s(x) • What kind of function is s(x)? • Heaviside Step Function: H(t) Shadow term for x’

  13. Convolution shadow map • Approximate shadow test with Fourier series c1 +c2 +..+c4 +..+c8 +..+c16

  14. c1 +c2 +..+c4 +..+c8 +..+c16 Convolution shadow map • Step function becomes sum of weighted sin() • Series is separable!

  15. Convolution • Bulid on convolution-based methods. • Simulate penumbrae by filtering shadows depending on the configuration of blocker, receiver, and light source.

  16. CSM order reduction • Annen et al[07] using a Fourier series to construct the f, but it’s prone to some artifacts and shadows at contact points may too bright.

  17. Outline • Introduction • Relate work • Convolution • Generation of Area Lights for Environment Maps • Limitations • Result

  18. Generation of Area Lights for Environment Maps

  19. Outline • Introduction • Relate work • Convolution • Illumination with Soft Shadows • Limitations • Result Ringing Suppression Textured light sources

  20. Outline • Introduction • Relate work • Convolution • Generation of Area Lights for Environment Maps • Limitations • Result • Conclusions and Future work 1. DirectX 10 2. Dual-Core AMD 2.2GHz 3. NVIDIA GeForce 8800 GTX graphics card

  21. Result • Buddha scene with 70k face MM: Mipmaps SAT: Summed area table

  22. Result

  23. Result • Performance of this paper and image quality depend on: • choice of prefilter • Number of area lights • Shadow map size

  24. Result • Demonstrate the effect of the sharpening function G().

  25. Result • Shows the influence of the number of light sources used for approximating the environment map.

  26. Outline • Introduction • Relate work • Convolution • Generation of Area Lights for Environment Maps • Limitations • Result • Conclusions and Future work Based on convolution. Fast enough to render many area light sources simul- taneously. Provide plausible results, even though they are not entirely physically correct. At future work, intend to explore the use area lights for indirect illumination.

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