A Layered, Heterogeneous Reflectance Model
for Acquiring and Rendering Human Skin
Craig Donner* Tim Weyrich†‡ Eugene d'Eon§ Ravi Ramamoorthi* Szymon Rusinkiewicz
*Columbia University Princeton University University College London §NVIDIA Corporation

To appear in ACM Transactions on Graphics (Proceedings of ACM SIGGRAPH Asia 2008).

Our model approximates heterogeneous light transport in skin through the inter-scattering of light between layers. Shown are hand-drawn spatially-varying parameter maps of two scattering layers, and of an infinitesimally thin absorbing layer between them. The maps have been scaled in intensity (10x for melanin, 20x for hemoglobin) to show detail. Given this simple input, our method renders heterogeneous and volumetric effects that cannot be simulated using previous methods.
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Example skin patch reconstructions (a,b,d,e,h,i) Caucasian, skin type III: bridge of the nose (a), freckle on arm (b) slight acne on arm (d), forehead (e), stronger acne on arm (h), scar on edge of the hand (i). (c,g) African, skin type V: exterior lower arm (c) (artifact due to hair), wrinkles at posterior side of wrist (g). (f) Caucasian, skin type II, exterior lower arm. (j) Asian-subcontinental, skin type IV, scar on back of hand. (k,l) Caucasian, red-haired, skin type I: exterior (k) and interior (l) lower arm.
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Chromophore concentrations as derived from our measurements, corresponding to patches in Figure to the left, (a--d).

Abstract

We introduce a layered, heterogeneous spectral reflectance model for human skin. The model captures the inter-scattering of light among layers, each of which may have an independent set of spatially-varying absorption and scattering parameters. For greater physical accuracy and control, we introduce an infinitesimally thin absorbing layer between scattering layers. To obtain parameters for our model, we use a novel acquisition method that begins with multi-spectral photographs. By using an inverse rendering technique, along with known chromophore spectra, we optimize for the best set of parameters for each pixel of a patch. Our method finds close matches to a wide variety of inputs with low residual error.

We apply our model to faithfully reproduce the complex variations in skin pigmentation. This is in contrast to most previous work, which assumes that skin is homogeneous or composed of homogeneous layers. We demonstrate the accuracy and flexibility of our model by creating complex skin visual effects such as veins, tattoos, rashes, and freckles, which would be difficult to author using only albedo textures at the skin's outer surface. Also, by varying the parameters to our model, we simulate effects from external forces, such as visible changes in blood flow within the skin due to external pressure.

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