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Lilong Shi and Brian Funt School of Computing Science, Simon Fraser University, Canada Skin Colour Imaging That Is Insensitive to Lighting Conditions

Lilong Shi and Brian Funt School of Computing Science, Simon Fraser University, Canada

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Lilong Shi and Brian Funt School of Computing Science, Simon Fraser University, Canada. Skin Colour Imaging That Is Insensitive to Lighting Conditions. Goal. Normalize skin tones of human faces E liminate the effects of illumination Preserve skin colour - PowerPoint PPT Presentation

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Page 1: Lilong  Shi and Brian  Funt School of Computing Science,  Simon Fraser University, Canada

Lilong Shi and Brian Funt

School of Computing Science, Simon Fraser University, Canada

Skin Colour Imaging That Is Insensitive to Lighting

Conditions

Page 2: Lilong  Shi and Brian  Funt School of Computing Science,  Simon Fraser University, Canada

Normalize skin tones of human faces

Eliminate the effects of illumination

Preserve skin colour

Allow variations of melanin concentration

Goal

Paper 102, slide [1/11] Paper 102 [Shi&Funt] ~2/11~

Page 3: Lilong  Shi and Brian  Funt School of Computing Science,  Simon Fraser University, Canada

Two-layered Skin Model [1] Epidermis Layer: Melanin Absorbance Dermis Layer: Hemoglobin Absorbance

A layer has properties of an optical filter

Skin Appearance

Paper 102 [Shi&Funt] ~3/11~

Page 4: Lilong  Shi and Brian  Funt School of Computing Science,  Simon Fraser University, Canada

4

Reflection spectrum of skin [1]:

where, ’s are pigment densities of melanin & hemoglobin ’s are absorbance of melanin and hemoglobin, l’s are mean path lengths of photons, is other scattering loss and absorbance.

Skin Model

)]()()()()(exp[)( hhhmmm llS

Paper 102, slide [3/11] Paper 102 [Shi&Funt] ~4/11~

Page 5: Lilong  Shi and Brian  Funt School of Computing Science,  Simon Fraser University, Canada

5

Wien’s blackbody radiation models

where, I is power of radiation, c1 and c2 are constants, T is blackbody temperature,

Illumination Model

Paper 102, slide [4/11]

Tc

eIcTE2

51),(

Paper 102 [Shi&Funt] ~5/11~

Page 6: Lilong  Shi and Brian  Funt School of Computing Science,  Simon Fraser University, Canada

6

Proposed to combine Skin & Illum. Models Assume narrowband sensors used:

In log space:

Then, let Π represent camera RGB:

Skin-Illum Model

Paper 102 [Shi&Funt] ~6/11~

},,{),,()( BGRiTESP iii

)]log(5)[log()log()(

)()()()()()log(

112

ii

iihihhimimmi

cITcllP

c1ωσσΠ bτb hhmmhm ),,,(

Page 7: Lilong  Shi and Brian  Funt School of Computing Science,  Simon Fraser University, Canada

7

where, m & h are melanin & hemoglobin bases, is a blackbody radiator basis, b = log(I), = 1/T, c is a constant vector.

m & h span all possible skin colours

Skin-Illum Model

Paper 102 [Shi&Funt] ~7/11~

c1ωσσΠ bτb hhmmhm ),,,(

σm

1

ωc

log G

log B

log R

σh

Page 8: Lilong  Shi and Brian  Funt School of Computing Science,  Simon Fraser University, Canada

8

Our simplified Skin-Illumination Model

For varying illumination colour temperature; For varying skin melanin concentration; m and span the chromaticity space of arbitrary skin under different illuminations.

Given a skin pixel, melanin concentration can be recovered, so is true skin colour.

Our Skin Model

Paper 102, slide [1/10]

ωσΠ τmmm ),(

Paper 102 [Shi&Funt] ~8/11~

Page 9: Lilong  Shi and Brian  Funt School of Computing Science,  Simon Fraser University, Canada

9

Results based on UOPB[2] database (#94)

(a) a series of 16 face images under different camera calibration and illumination conditions. (faces segmented from the background) (b) the same images with corrected

skin tones based on our model.

Experiments

Paper 102 [Shi&Funt] ~9/11~

Page 10: Lilong  Shi and Brian  Funt School of Computing Science,  Simon Fraser University, Canada

10

Results based on UOPB[2] database (#111)

(a) a series of 16 face images under different camera calibration and illumination conditions. (faces segmented from the background) (b) the same images with corrected

skin tones based on our model.

Experiments

Paper 102 [Shi&Funt] ~10/11~

Page 11: Lilong  Shi and Brian  Funt School of Computing Science,  Simon Fraser University, Canada

11

Based on physical models Estimate skin melanin concentration Skin colour varies along melanin axis Shift colour along illum. axis Simple and computationally inexpensive

References: [1] Shimada, M., Y. Yamada, M. Itoh and T. Yatagai. 2001. Melanin and blood concentration in a human skin model studied by multiple regression analysis: assessment by Monte Carlo simulation. Phys. Med. Biol. 46(9):2397-2406.

[2] Marszalec, E., B. Martinkauppi, M. Soriano, M. Pietikäinen. 2000. A physics-based face database for color research. Journal of Electronic Imaging 9(1):32-38.

Conclusion

Paper 102, slide [5/11] Paper 102 [Shi&Funt] ~11/11~