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A Common Framework for Ambient Illumination in the Dichromatic Reflectance Model

A Common Framework for Ambient Illumination in the Dichromatic Reflectance Model. Color and Reflectance in Imaging and Computer Vision Workshop 2009 October 4, 2009. Christian Riess Johannes Jordan Prof. Elli Angelopoulou Pattern Recognition Lab (CS 5) University of Erlangen-Nuremberg.

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A Common Framework for Ambient Illumination in the Dichromatic Reflectance Model

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  1. A Common Framework for Ambient Illumination in the Dichromatic Reflectance Model Color and Reflectance in Imaging and Computer Vision Workshop 2009October 4, 2009 Christian Riess Johannes Jordan Prof. Elli Angelopoulou Pattern Recognition Lab (CS 5) University of Erlangen-Nuremberg

  2. Natural Images: Shadows, Interreflections • Typical assumption in Color Constancy and Illuminant Color Estimation: One single illuminant. • Consider a challengingimage:Multiple light sources,shadows, inter-reflections. • Maybe we need amore complex model?

  3. Common Reflectance Models • Lambertian Reflectance: Ideal Diffuse Reflectance • Dichromatic Reflectance Model [1]: Specular and Diffuse Wave length Directions of incidence on surface and exitance towards viewer Surface radiance Geometric terms Surface reflectance (albedo) Direct illuminant [1] S. Shafer. Using Color to Separate Reflection Components. Color Research Application, pp. 210-218, 1985.

  4. Bi-Illuminant Dichromatic Reflection Model [1] Direct light, specular refl. Direct light, diffuse refl. Ambient light, specular refl. Ambient light, diffuse refl. Wave length Directions of incidence on surface and exitance towards viewer Surface radiance Geometric terms Surface reflectance (albedo) Direct illuminant Diffuse illuminant [1] B. Maxwell, R. Friedhoff, and C. Smith. A Bi-Illuminant Dichromatic Reflection Model for Understanding Images. Computer Vision and Pattern Recognition, pp. 1-8, 2008.

  5. The Ambient Term • The BIDR contains a very flexible “catch all” ambient term. • For practical exploitation, further constraints have to be made • These constraints can form a taxonomy of illumination-related techniques

  6. BIDR as a General Framework (I) • Shadow Boundaries: Learning illuminant ratios [1] • Channelwise relative attenuation of the direct illuminant • Isotropic ambient light • Weighting factor between direct and ambient light Split illuminant into chromaticand energy part Make ambientlight isotropic Excludespecularities Attenuatedirect illuminant [1] K. Barnard and G. Finlayson. Shadow Identification using Colour Ratios. IS&T/SID 8th Colour Imaging Conference: Colour Science, Systems and Applications, pp. 97-101, 2000.

  7. BIDR as a General Framework (II) • Scene Illuminant Estimation with Flash/No-Flash Images [1] • Consider normal illumination as ambient light, flash is direct light • Knowledge of the flash light characteristics resolves the scene parameters • Flash image: • Non-Flash image: • Difference of log-chromaticities recovers average ambient light Excludespecularities Assume Planckianilluminant, flashlight is known [1] C. Lu and M. Drew. Practical Scene Illuminant Estimation via Flash/No-Flash Pairs. IS&T/SID 14th Colour Imaging Conference: Colour Science, Systems and Applications, 2006.

  8. Experiments: Setup • Is the consideration of such a model justified at all? • -> only if ambient illumination is complicated enough to disturb our analysis • Chalk (sort-of Lambertian), direct light, ambient light and a combination of direct and ambient light. Direct illumination Ambient illumination Direct and ambientillumination

  9. Experiments: Expectations • Dichromatic Reflectance under laboratory conditions • With additional (more or less uniform) ambient lighting, we would expect the line to be rotated and/or shifted: Specular triangle Specular triangle Diffuse Line Diffuse Line RGB Cube RGB Cube

  10. Experiments: Results • Diffuse and ambient pixels “almost” linearly distributedin RGB space:

  11. Experiments: Results Characteristicspots on chalk pixels Chalk: regions of interest Per-pixel contributionof each illuminant Blue Red Green

  12. Conclusion and Outlook • Dichromatic Reflection Model is limited to a single light source, making several real-world images difficult to analyze • Outdoor scenes • (Partially) shadowed areas • Natural extension: Bi-Illuminant Dichromatic Reflectance Model • A common framework for modelling shadows, interreflections or a second direct illuminant • Experiments on real-world images demonstrate the need for more complex assumptions • Outlook: Develop new illumination estimation algorithms based on less constraining assumptions

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