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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

A Common Framework for Ambient Illumination in the Dichromatic Reflectance Model Color and Reflectance in Imaging and Computer Vision Workshop 2009 October

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Page 1: A Common Framework for Ambient Illumination in the Dichromatic Reflectance Model Color and Reflectance in Imaging and Computer Vision Workshop 2009 October

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 RiessJohannes Jordan

Prof. Elli Angelopoulou

Pattern Recognition Lab (CS 5)

University of Erlangen-Nuremberg

Page 2: A Common Framework for Ambient Illumination in the Dichromatic Reflectance Model Color and Reflectance in Imaging and Computer Vision Workshop 2009 October

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C. RiessOctober 4, 2009 A Common Framework for Ambient Illumination in the Dichromatic Reflectance Model

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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?

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C. RiessOctober 4, 2009 A Common Framework for Ambient Illumination in the Dichromatic Reflectance Model

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Lambertian Reflectance: Ideal Diffuse Reflectance

Dichromatic Reflectance Model [1]: Specular and Diffuse

Common Reflectance Models

[1] S. Shafer. Using Color to Separate Reflection Components. Color Research Application, pp. 210-218, 1985.

Wave length

Directions of incidence on surface and exitance towards viewer

Surface radiance

Geometric terms

Surface reflectance (albedo)

Direct illuminant

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C. RiessOctober 4, 2009 A Common Framework for Ambient Illumination in the Dichromatic Reflectance Model

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Bi-Illuminant Dichromatic Reflection Model [1]

[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.

Wave length

Directions of incidence on surface and exitance towards viewer

Surface radiance

Geometric terms

Surface reflectance (albedo)

Direct illuminant

Diffuse illuminant

Direct light, specular refl. Direct light, diffuse refl.

Ambient light, specular refl. Ambient light, diffuse refl.

Page 5: A Common Framework for Ambient Illumination in the Dichromatic Reflectance Model Color and Reflectance in Imaging and Computer Vision Workshop 2009 October

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C. RiessOctober 4, 2009 A Common Framework for Ambient Illumination in the Dichromatic Reflectance Model

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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

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C. RiessOctober 4, 2009 A Common Framework for Ambient Illumination in the Dichromatic Reflectance Model

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BIDR as a General Framework (I)

[1] K. Barnard and G. Finlayson. Shadow Identification using Colour Ratios. IS&T/SID 8 th Colour Imaging Conference: Colour Science, Systems and Applications, pp. 97-101, 2000.

Shadow Boundaries: Learning illuminant ratios [1] Channelwise relative attenuation of the direct illuminant

Isotropic ambient light

Weighting factor between direct and ambient light

Excludespecularities

Make ambientlight isotropic

Split illuminantinto chromatic

and energy part

Attenuatedirect illuminant

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C. RiessOctober 4, 2009 A Common Framework for Ambient Illumination in the Dichromatic Reflectance Model

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BIDR as a General Framework (II)

[1] C. Lu and M. Drew. Practical Scene Illuminant Estimation via Flash/No-Flash Pairs. IS&T/SID 14 th Colour Imaging Conference: Colour Science, Systems and Applications, 2006.

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

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C. RiessOctober 4, 2009 A Common Framework for Ambient Illumination in the Dichromatic Reflectance Model

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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.

Ambient illumination Direct and ambientillumination

Direct illumination

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C. RiessOctober 4, 2009 A Common Framework for Ambient Illumination in the Dichromatic Reflectance Model

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Dichromatic Reflectance under laboratory conditions

With additional (more or less uniform) ambient lighting, we would expect the line to be rotated and/or shifted:

Experiments: Expectations

Diffuse Line

Specular triangle

RGB Cube

Diffuse Line

Specular triangle

RGB Cube

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C. RiessOctober 4, 2009 A Common Framework for Ambient Illumination in the Dichromatic Reflectance Model

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Experiments: Results

Diffuse and ambient pixels “almost” linearly distributedin RGB space:

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C. RiessOctober 4, 2009 A Common Framework for Ambient Illumination in the Dichromatic Reflectance Model

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Experiments: Results

RedGreen

Blue

Chalk: regions of interest

Characteristic

spots on chalk pixels

Per-pixel contributionof each illuminant

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C. RiessOctober 4, 2009 A Common Framework for Ambient Illumination in the Dichromatic Reflectance Model

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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