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Real-Time All-Frequency Soft Shadows in Dynamic Scenes Using Area Light Generation

This paper discusses a method for rendering real-time soft shadows in dynamic scenes, utilizing area lights and environment maps. The primary contribution is the ability to create plausible soft shadows while supporting both area and environment lighting. The approach involves convolution techniques, precomputation, and simplifications to facilitate fast rendering. Limitations are acknowledged, including challenges with dynamic scenes and arbitrary illumination. Future work will explore the integration of area lights for indirect illumination, aiming to improve the realism and efficiency of the rendering process.

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Real-Time All-Frequency Soft Shadows in Dynamic Scenes Using Area Light Generation

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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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