Abstract
Skin colour forms a curved manifold in RGB space. The variations in skin colour are largely caused by variations in concentration of the pigments melanin and hemoglobin. Hence, linear statistical models of appearance or skin albedo are insufficiently constrained (they can produce implausible skin tones) and lack compactness (they require additional dimensions to linearly approximate a curved manifold). In this paper, we propose to use a biophysical model of skin colouration in order to transform skin colour into a parameter space where linear statistical modelling can take place. Hence, we propose a hybrid of biophysical and statistical modelling. We present a two parameter spectral model of skin colouration, methods for fitting the model to data captured in a lightstage and then build our hybrid model on a sample of such registered data. We present face editing results and compare our model against a pure statistical model built directly on textures.