Efficient Estimation of Spatially Varying Subsurface Scattering Parameters for Relighting (bibtex)
by Sarah Tariq, Andrew Gardner, Ignacio Llamas, Andrew Jones, Paul Debevec, Greg Turk
Abstract:
We present an image-based technique to rapidly ac- quire spatially varying subsurface reflectance prop- erties of a human face. The estimated properties can be used directly to render faces with spatially vary- ing scattering, or can be used to estimate a robust average across the face. We demonstrate our tech- nique with renderings of peoples' faces under novel, spatially-varying illumination and provide compar- isons with current techniques. Our captured data consists of images of the face from a single view- point under two small sets of projected images. The first set, a sequence of phase shifted periodic stripe patterns, provides a per-pixel profile of how light scatters from adjacent locations. The second set contains structured light and is used to obtain face geometry. We match the observed reflectance pro- files to scattering properties predicted by a scatter- ing model using a lookup table. From these prop- erties we can generate images 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 for Relighting (Sarah Tariq, Andrew Gardner, Ignacio Llamas, Andrew Jones, Paul Debevec, Greg Turk), 2006.
Bibtex Entry:
@techreport{tariq_efficient_2006,
	type = {{ICT} {Technical} {Report}},
	title = {Efficient {Estimation} of {Spatially} {Varying} {Subsurface} {Scattering} {Parameters} for {Relighting}},
	url = {http://ict.usc.edu/pubs/ICT-TR-01-2006.pdf},
	abstract = {We present an image-based technique to rapidly ac- quire spatially varying subsurface reflectance prop- erties of a human face. The estimated properties can be used directly to render faces with spatially vary- ing scattering, or can be used to estimate a robust average across the face. We demonstrate our tech- nique with renderings of peoples' faces under novel, spatially-varying illumination and provide compar- isons with current techniques. Our captured data consists of images of the face from a single view- point under two small sets of projected images. The first set, a sequence of phase shifted periodic stripe patterns, provides a per-pixel profile of how light scatters from adjacent locations. The second set contains structured light and is used to obtain face geometry. We match the observed reflectance pro- files to scattering properties predicted by a scatter- ing model using a lookup table. From these prop- erties we can generate images 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.},
	number = {ICT TR 01 2006},
	institution = {University of Southern California Institute for Creative Technologies},
	author = {Tariq, Sarah and Gardner, Andrew and Llamas, Ignacio and Jones, Andrew and Debevec, Paul and Turk, Greg},
	year = {2006},
	keywords = {Graphics}
}
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