1. Real-Time Rendering Digital Image Synthesis Yung-Yu Chuang 01/03/2006 with slides by Ravi Ramamoorthi and Robin Green

2. Realistic rendering So far, we have talked photorealistic rendering including complex materials, complex geometry and complex lighting. They are slow.

3. Real-time rendering Goal is to achieve interactive rendering with reasonable quality. It ’ s important in many applications such as games, visualization, computer-aided design, …

4. Basic themes Interactive ray-tracing Programmable graphics hardware Image-based rendering Precomputation-based methods

5. Natural illumination People perceive materials more easily under natural illumination than simplified illumination. Images courtesy Ron Dror and Ted Adelson

6. Natural illumination Classically, rendering with natural illumination is very expensive compared to using simplified illumination directional source natural illumination

7. Reflection maps Blinn and Newell, 1976

8. Environment maps Miller and Hoffman, 1984

9. HDR lighting

10. Examples

13. Complex illumination

14. Basis Functions are pieces of signal that can be used to produce approximations to a function Basis functions

15. We can then use these coefficients to reconstruct an approximation to the original signal Basis functions

16. We can then use these coefficients to reconstruct an approximation to the original signal Basis functions

17. Orthogonal basis functions Orthogonal Basis Functions –These are families of functions with special properties –Intuitively, it’s like functions don’t overlap each other’s footprint A bit like the way a Fourier transform breaks a functions into component sine waves

18. Basis functions Transform data to a space in which we can capture the essence of the data better Here, we use spherical harmonics, similar to Fourier transform in spherical domain

19. Real spherical harmonics A system of signed, orthogonal functions over the sphere Represented in spherical coordinates by the function where l is the band and m is the index within the band

20. Real spherical harmonics

21. Reading SH diagrams – + Not this direction This direction

22. Reading SH diagrams – + Not this direction This direction

23. The SH functions

25. Spherical harmonics

26. -2012 0 1 2 m l

27. SH projection First we define a strict order for SH functions Project a spherical function into a vector of SH coefficients

28. SH reconstruction To reconstruct the approximation to a function We truncate the infinite series of SH functions to give a low frequency approximation

29. Examples of reconstruction

30. An example Take a function comprised of two area light sources –SH project them into 4 bands = 16 coefficients

31. Low frequency light source We reconstruct the signal –Using only these coefficients to find a low frequency approximation to the original light source

32. SH lighting for diffuse objects An Efficient Representation for Irradiance Environment Maps, Ravi Ramamoorthi and Pat Hanrahan, SIGGRAPH 2001 Assumptions –Diffuse surfaces –Distant illumination –No shadowing, interreflection irradiance is a function of surface normal

33. Diffuse reflection radiosity (image intensity) reflectance (albedo/texture) irradiance (incoming light) × = quake light map

34. Irradiance environment maps Illumination Environment Map Irradiance Environment Map L n

35. Spherical harmonic expansion Expand lighting (L), irradiance (E) in basis functions =.67+.36+ …

36. Analytic irradiance formula Lambertian surface acts like low-pass filter 0 01 2 cosine term

37. 9 parameter approximation Exact image Order 0 1 term RMS error = 25 % -201 2 0 1 2 l m

38. 9 Parameter Approximation Exact image Order 1 4 terms RMS Error = 8% -201 2 0 1 2 l m

39. 9 Parameter Approximation Exact image Order 2 9 terms RMS Error = 1% For any illumination, average error < 3% [Basri Jacobs 01] -201 2 0 1 2 l m

40. Comparison Incident illumination 300x300 Irradiance map Texture: 256x256 Hemispherical Integration 2Hrs Irradiance map Texture: 256x256 Spherical Harmonic Coefficients 1sec

41. Rendering Irradiance approximated by quadratic polynomial Surface Normal vector column 4-vector 4x4 matrix (depends linearly on coefficients L lm )

42. Complex geometry Assume no shadowing: Simply use surface normal

43. Video