Simon Fraser UniversityComputational Vision Lab
Lilong Shi, Brian Funt and Tim Lee
Studies of factors affecting skin colour
Simple and linear model of skin
Modelling Skin appearance under lights
Applications: Estimate melanin and hemoglobin
concentrations Correct imaged skin tones for lighting
conditions
Tone correctio
n
Preserve melanin
Skin tone correction
Melanin/Hemoglobin separation
Appearance of human skin determined by Biological factors
▪ pigmentation, blood microcirculation, roughness, etc..
Viewing conditions▪ Inducing lights
Acquisition devices▪ Cones in retina, RGB sensors of CCD digital cameras
Two-layered Skin Model [2] Epidermis Layer: melanin absorbance Dermis Layer: hemoglobin absorbance
A layer has properties of an optical filter
Various skin colour <= melanin +
hemoglobin Genetic: Race Temporary:
▪ Exposure to UV ▪ Hot bath
Mixture varying by 2 independent factors Analyse melanin and hemoglobin factors
Estimate melanin and hemoglobin
concentration
Independent Component Analysis (ICA)– Statistical technique for revealing “hidden”
factors– To “unmix” or “separate” signals composed of
multiple sources– Independent and linear mixing– Related to Eigen-vector analysis
Original Source Signals Observed SignalsMixing
s1
s2
70%
30%
v1
s × A = v
20%
80%
v20%
100%
v3
Melanin
Hemoglobin
Skin samples
Melanin
Hemoglobin
Typical skin spectrum Visible wavelength 400nm – 700nm
Extract skin bases from observed spectrum by ICA
ICA
(left) 33 skin spectrum after normalization; (right) two independent basis spectrum – the melanin and hemoglobin, and the spectrum of chromophores other than melanin and hemoglobin pigments.
Arbitrary skin spectrum can be approximated cσσ hhmm
constru
are variableshm ,
Human vision▪ 3 types of
Photoreceptors L, M and S Cones
Digital Cameras▪ 3 sensors
Red, Green, and Blue
Reflectance spectrum recorded by 3 sensors => three values (R, G, B) for a skin colour
cσσpixel hhmm
Possible skin colours lie within plane
Given a pixel from
skin, compute
by projecting
log(R,G,B) onto
hm ,
hm σσ ,
Input Image [3]
Melanin Image
Hemoglobin Image
m
h
cσσ hhmm
- Inverse melanin concentration- Inverse hemoglobin concentration
Skin appearance greatly affected by lights
Reveal true skin colour by removing illum.
Common lights blackbody radiation e.g. tungsten/halogen lamps, sunrise/sunset, etc Varying colour temperature T
▪ Redish -> white -> bluish
Colour: illumination times reflectance
In log space, multiplication => addition:
cωσσΠ τhhmmhm ),,(
Illum. basis
In practice
Drop hemoglobin basis ▪ Small angle between Illum and hemoglobin axes
Ignore brightness Skin colour varying by T and
( , )m m m τ Π σ ω
m
384 real skin reflectances times 67 real light sources
=> 25728 samples
( , )m m m τ Π σ ω
Skin tone correction example (UOPB DB [4])
20
Tone correction
Preserve melanin
16 different illumination +
camera settings
• Skin tone correction example (UOPB DB [4])
Skin colour modelling: Melanin and Hemoglobin concentration Linear model in logarithm space Estimation by Independent Component
Analysis Skin appearance + Light modelling:
Estimates light source Preserves skin colour by melanin value
Applied to digital images from CCD cameras
[1] Shi, L., and Funt, B., "Skin Colour Imaging That Is Insensitive to Lighting," Proc. AIC (Association Internationale de la Couleur) Conference on Colour Effects & Affects, Stockholm, June 2008
[2] Angelopoulou, E., Molana, R., and Daniilidis, K. “Multispectral skin color modeling,” In IEEE Conf. on Computer Vision and Pattern Recognition, volume 2, pages 635-642, Kauai, Hawaii, Dec. 2001.
[3] Shimizu, H., Uetsuki, K., Tsumura, N., and Miyake, Y. Analyzing the effect of cosmetic essence by independent component analysis for skin color images. In 3rd Int. Conf. on Multispectral Color Science, pages 65-68, Joensuu, Finland, June 2001.
[4] Martinkauppi, B. “Face color under varying illumination-analysis and applications,” Ph.D. Dissertation, University of Oulu, 2002.
Top Related