Efficient Estimation of Spatially Varying Subsurface Scattering Parameters (bibtex)
by Sarah Tariq, Andrew Gardner, Ignacio Llamas, Andrew Jones, Paul Debevec, Greg Turk
Abstract:
We present an image-based technique to efficiently acquire spatially varying subsurface reflectance properties of a human face. The estimated prop- erties can be used directly to render faces with spa- tially varying scattering, or can be used to estimate a robust average across the face. We demonstrate our technique with renderings of peoples' faces un- der novel, spatially-varying illumination and pro- vide comparisons with current techniques. Our cap- tured data consists of images of the face from a sin- gle viewpoint under two small sets of projected im- ages. The first set, a sequence of phase-shifted pe- riodic stripe patterns, provides a per-pixel profile of how light scatters from adjacent locations. The sec- ond set of structured light patterns is used to obtain face geometry. We subtract the minimum of each profile to remove the contribution of interreflected light from the rest of the face, and then match the observed reflectance profiles to scattering properties predicted by a scattering model using a lookup ta- ble. From these properties we can generate images of the subsurface reflectance of the face under any incident illumination, including local lighting. The rendered images exhibit realistic subsurface trans- port, including light bleeding across shadow edges. Our method works more than an order of magnitude faster than current techniques for capturing subsur- face scattering information, and makes it possible for the first time to capture these properties over an entire face.
Reference:
Efficient Estimation of Spatially Varying Subsurface Scattering Parameters (Sarah Tariq, Andrew Gardner, Ignacio Llamas, Andrew Jones, Paul Debevec, Greg Turk), In 11th International Fall Workshop on Vision, Modeling and Visualization, 2006.
Bibtex Entry:
@inproceedings{tariq_efficient_2006-1,
	address = {Aachen, Germany},
	title = {Efficient {Estimation} of {Spatially} {Varying} {Subsurface} {Scattering} {Parameters}},
	url = {http://ict.usc.edu/pubs/Efficient%20Estimation%20of%20Spatially%20Varying%20Subsurface%20Scattering%20Parameters.pdf},
	abstract = {We present an image-based technique to efficiently acquire spatially varying subsurface reflectance properties of a human face. The estimated prop- erties can be used directly to render faces with spa- tially varying scattering, or can be used to estimate a robust average across the face. We demonstrate our technique with renderings of peoples' faces un- der novel, spatially-varying illumination and pro- vide comparisons with current techniques. Our cap- tured data consists of images of the face from a sin- gle viewpoint under two small sets of projected im- ages. The first set, a sequence of phase-shifted pe- riodic stripe patterns, provides a per-pixel profile of how light scatters from adjacent locations. The sec- ond set of structured light patterns is used to obtain face geometry. We subtract the minimum of each profile to remove the contribution of interreflected light from the rest of the face, and then match the observed reflectance profiles to scattering properties predicted by a scattering model using a lookup ta- ble. From these properties we can generate images of the subsurface reflectance of the face under any incident illumination, including local lighting. The rendered images exhibit realistic subsurface trans- port, including light bleeding across shadow edges. Our method works more than an order of magnitude faster than current techniques for capturing subsur- face scattering information, and makes it possible for the first time to capture these properties over an entire face.},
	booktitle = {11th {International} {Fall} {Workshop} on {Vision}, {Modeling} and {Visualization}},
	author = {Tariq, Sarah and Gardner, Andrew and Llamas, Ignacio and Jones, Andrew and Debevec, Paul and Turk, Greg},
	month = jun,
	year = {2006},
	keywords = {Graphics}
}
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