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HDRI & Applications (Image Based Rendering)

HDRI & Applications (Image Based Rendering). Image-Based Rendering from a Single Image - INRIA 2001. Inverse Global Illumination: Recovering Reflectance Models of Real Scenes from Photographs – SIGGRAPH99. Diffuse reflectance Model. Specular Parameters. L i is radiance at P i.

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HDRI & Applications (Image Based Rendering)

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  1. HDRI & Applications (Image Based Rendering)

  2. Image-Based Rendering from a Single Image- INRIA 2001

  3. Inverse Global Illumination: Recovering Reflectance Models of Real Scenes from Photographs – SIGGRAPH99

  4. Diffuse reflectance Model

  5. Specular Parameters • Li is radiance at Pi • Ii is irradiance at Pi • Qiis light & camera position • 3 or 5 unknown parameters: ρd, ρs and a

  6. Mutual Illumination  This is purely due to specularity

  7. Mutual Illumination • Idea for iterative algorithm: • assume zero ΔS initially • do • calculate L radiances from ΔS estimates usingglobal illumination • update all ρd, ρs, a using L radiances • re-estimate ΔS using ρd, ρs, a and L • loop until convergence

  8. Irradiance of Surfaces Irradiance of Film Radoisity of Surfaces Recovering High Dynamic Range Image from Photograph – SIGGRAPH97

  9. The Algorithm Zij = f(EiΔtj ) f -1(Zij) = EiΔtj ln f-1 (Zij) = lnEi + lnΔtj g = ln f-1g(Zij) = lnEi + lnΔtj Unknowns : irradiance Ei and function g (assume g is smooth & monotonic)

  10. The Algorithm g(Zij) = lnEi + lnΔtj The second term is a smoothness term g'' (z) = g(z-1) - 2g(z) + g(z+1) where, scalarλweights relative to the data fitting term and be chosen for the amount of noise expected in the Zij

  11. Recover Camera Response Curve Δt = 2″ Δt = 0.1″ Δt = 1″ Δt = 0.5″ Δt =0.05″ Δt = 0.025″ Δt = 0.0125″ Δt = 0.00625″ Δt = 0.003215″ Δt = 0.001562″

  12. Extraction of Bump Maps from HDRI

  13. HDRI Processing

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