Image-Based Lighting in Computational Photography

Explore the techniques and concepts of image-based lighting in computational photography through slides covering topics such as rendering objects in images, using environment maps and light probes, mirrored spheres, and dealing with light sources like the sun. Learn about capturing and utilizing light data to enhance visual realism in digital imagery.

• Computational Photography
• Image-Based Lighting
• Rendering Techniques
• Environment Maps
• Light Probes

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1. COMP790: Computational Photography Image-Based Lighting Montek Singh Apr 17, 2019 (Credits to numerous other people on individual slides)

2. Next section of slides mainly from Derek Hoiem, and transitively from Debevec, some Efros, and Kevin Karsch. Note many other sources for individual slides.

3. Image-based Lighting T2 Slide from Derek Hoiem

4. How to render an object inserted into an image? Image-based lighting Capture incoming light with a light probe Model local scene Ray trace, but replace distant scene with info from light probe Debevec SIGGRAPH 1998

5. Key ideas for Image-based Lighting Environment maps: tell what light is entering at each angle within some shell +

6. Spherical Map Example

7. Key ideas for Image-based Lighting Light probes: a way of capturing environment maps in real scenes

8. Mirrored Sphere

9. 1) Compute normal of sphere from pixel position 2) Compute reflected ray direction from sphere normal 3) Convert to spherical coordinates (theta, phi) 4) Create equirectangular image

10. Mirror ball -> equirectangular

11. Mirror ball -> equirectangular Mirror ball Normals Reflection vectors Phi/theta of reflection vecs Phi/theta equirectangular domain Equirectangular

12. One small snag How do we deal with light sources? Sun, lights, etc? They are much, much brighter than the rest of the environment Relative Brightness . 1907 . 46 . 15116 . 1 . 18 Use High Dynamic Range photography!

13. Key ideas for Image-based Lighting Capturing HDR images: needed so that light probes capture full range of radiance

14. LDR->HDR by merging exposures 0 to 255 Exposure 1 Exposure 2 Exposure n 10-6 106 Real world High dynamic range

15. The Math Let g(z) be the discrete inverse response function For each pixel site i in each image j, want: ln Radiancei+ln tj= g(Zij) Solve the overdetermined linear system: Z N P max = i 1 = Z 2 + + 2 ln ln ( ) ( ) Radiance t g Z g z i j ij = 1 j z min fitting term smoothness term

16. Reconstructed radiance map

17. Acquiring the Light Probe

18. Assembling the Light Probe

19. Real-World HDR Lighting Environments Funston Beach Eucalyptus Grove Grace Cathedral Uffizi Gallery Lighting Environments from the Light Probe Image Gallery: http://www.debevec.org/Probes/

20. Illumination Results

21. CG Objects Illuminated by a Traditional CG Light Source

22. Illuminating Objects using Measurements of Real Light Environment assigned glow material property in Greg Ward s RADIANCE system. Light Object http://radsite.lbl.gov/radiance/

23. Paul Debevec. A Tutorial on Image-Based Lighting. IEEE Computer Graphics and Applications, Jan/Feb 2002.

24. Rendering with Natural Light SIGGRAPH 98 Electronic Theater

25. Movie http://www.youtube.com/watch?v=EHBgkeXH9lU

26. Illuminating a Small Scene

28. We can now illuminate synthetic objects with real light. - Environment map - Light probe - HDR - Ray tracing How do we add synthetic objects to a real scene?

29. Real Scene Example Goal: place synthetic objects on table

30. Modeling the Scene light-based model real scene

31. Light Probe / Calibration Grid

32. The Light-Based Room Model

33. Modeling the Scene light-based model local scene synthetic objects real scene

34. The Lighting Computation distant scene (light-based, unknown BRDF) synthetic objects (known BRDF) local scene (estimated BRDF)

35. Rendering into the Scene Background Image

36. Differential Rendering Local scene w/o objects, illuminated by model

37. Rendering into the Scene Objects and Local Scene matched to Scene

38. Differential Rendering Difference in local scene - =

39. Differential Rendering Final Result

40. IMAGE-BASED LIGHTING INFIAT LUX Paul Debevec, Tim Hawkins, Westley Sarokin, H. P. Duiker, Christine Cheng, Tal Garfinkel, Jenny Huang SIGGRAPH 99 Electronic Theater

41. Fiat Lux http://ict.debevec.org/~debevec/FiatLux/movie/ http://ict.debevec.org/~debevec/FiatLux/technology/

42. What if we dont have a light probe? Zoom in on eye Insert Relit Face Environment map from eye http://www1.cs.columbia.edu/CAVE/projects/world_eye/ -- Nishino Nayar 2004

44. Environment Map from an Eye

45. Can Tell What You are Looking At huris8shrinkEye Image: alexinput Computed Retinal Image:

46. Summary Real scenes have complex geometries and materials that are difficult to model We can use an environment map, captured with a light probe, as a replacement for distance lighting We can get an HDR image by combining bracketed shots We can relight objects at that position using the environment map