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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. Goal. Normalize skin tones of human faces E liminate the effects of illumination Preserve skin colour

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

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

  2. Goal Normalize skin tones of human faces Eliminate the effects of illumination Preserve skin colour Allow variations of melanin concentration Paper 102 [Shi&Funt] ~2/11~ Paper 102, slide [1/11]

  3. Skin Appearance • Two-layered Skin Model [1] • Epidermis Layer: Melanin Absorbance • Dermis Layer: Hemoglobin Absorbance • A layer has properties of an optical filter Paper 102 [Shi&Funt] ~3/11~

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

  5. IlluminationModel • Wien’s blackbody radiation models • where, • I is power of radiation, • c1 and c2 are constants, • T is blackbody temperature, Paper 102 [Shi&Funt] ~5/11~ Paper 102, slide [4/11]

  6. Skin-Illum Model Proposed to combine Skin & Illum. Models Assume narrowband sensors used: In log space: Then, let Π represent camera RGB: Paper 102 [Shi&Funt] ~6/11~

  7. log G 1 σm σh c ω log R log B Skin-Illum Model 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 Paper 102 [Shi&Funt] ~7/11~

  8. Our Skin Model • 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. Paper 102 [Shi&Funt] ~8/11~ Paper 102, slide [1/10]

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

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

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

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