Computer Graphics

1. Lecture Notes #16 Image-BasedLighting Computer Graphics

2. Global Illumination and Image-Based Lighting • Traditional Computer Graphics involves: • Modelling with matter: geometry with reflectance properties. • Image-Based Lighting allows: • Combination of real and synthetic graphics with consistent illumination, using images as light sources. • Extension of Environment mapping

3. Environment Mapping • Computing the color according to the reflection vector • No self-shadowing, no inter-reflection

4. Image Based Lighting • Add models or objects to scenes and allow them to be manipulated in the scenes. • Modelling with light allows added objects to be illuminated consistent with image existent lighting - photorealistic inclusions. • We start with the answer by finding the scene illumination.

5. Image Based Lighting (all pictures P. Debevec 98-99)‏ • Real Scene • Goal: place synthetic objects on table

6. Extracting scene lighting • Capture illumination using illumination sphere

7. Image Based Lighting Real scene

8. Image Based Lighting captured illumination field

9. Image Based Lighting light based model synthetic objects local scene Real scene

10. Image Based Lighting • Use global illumination - compute effects of synthetic objects on local scene light based model synthetic objects (brdf known)‏ local scene (brdf estimated)‏

11. Image Based Lighting • Render into the scene background

12. Image Based Lighting • Render synthetic objects

13. Image Based Lighting • Effect of local scene on real scene

14. Image Based Lighting • Add differences to image

15. Some more results

16. Light Probe Images • Spherical Environment Maps • In most digital images, pixel values aren’t proportional to the light levels in the scene. • light levels are encoded nonlinearly so they appear either more correctly or more pleasingly on CRTs

17. High-Dynamic Range Photography • Standard digital images typically represent only a small fraction of the dynamic range—the ratio between the dimmest and brightest regions accurately represented—present in most realworld lighting environments. • The bright light saturates the pixel colour • Need a high dynamic range image which can be produced by combining images of different shutter speed

18. High-Dynamic Range Photography

19. HDR images

21. Comparison: Radiance mapversus single image

22. Eyes For Relighting • Extracting environment maps from eyes for use in integrating and relighting scenes • Apply IBL to the 3D objects added into the image • http://www.youtube.com/watch?v=MllTSofXt8E

23. Object Shape from Shading • Obtaining the 3D shape from an image • Assuming Lambertian reflection • Can recover the normal vector if we cast the light from 3 different directions Example: sphere (lit from left)‏ N  L

24. Integrate the normals over the surface to compute the 3D surface • We can also estimate the colour information and use this for texture

25. Surface inserted into new scenes • lit according to the global illumination of that scene. • This illumination can of course come from eyes!

26. Acquiring the Reflectance Field of a Human Face • Simulating reflectance on human faces requires a lot of effort and computation • Need to acquire the reflectance model • Subsurface scattering • Instead of simulating the global illumination, we can simply illuminate the face by real-lights from different directions • Creating images of arbitrary light conditions by combining the captured data

27. The Light Stage:60-second exposure

28. Original Resolution: 6432 Light Stage Data Lighting through image recombination: Haeberli ‘92, Nimeroff ‘94, Wong ‘97

29. Reflectance Functions

30. 1 Lighting Reflectance Functions normalized light map reflectance function lighting product rendered pixel

31. References • Rendering Synthetic Objects into Real Scenes, SIGGRAPH 98 • Acquiring the Reflectance Field of a Human Face, SIGGRAPH 2000 http://www.debevec.org • Eyes For Relighting, Nishino SIGGRAPH 2004