Temporal Upsampling of Performance Geometry using Photometric Alignment (bibtex)
by Cyrus A. Wilson, Abhijeet Ghosh, Pieter Peers, Jen-Yuan Chiang, Jay Busch, Paul Debevec
Abstract:
We present a novel technique for acquiring detailed facial geometry of a dynamic performance using extended spherical gradient illumination. Key to our method is a new algorithm for jointly aligning two photographs – under a gradient illumination condition and its complement – to a full-on tracking frame, providing dense temporal correspondences under changing lighting conditions. We employ a two step algorithm to reconstruct detailed geometry for every captured frame. In the first step, we coalesce information from the gradient illumination frames to the full-on tracking frame, and form a temporally aligned photometric normal map, which is subsequently combined with dense stereo correspondences yielding a detailed geometry. In a second step, we propagate the detailed geometry back to every captured instance guided by the previously computed dense correspondences. We demonstrate reconstructed dynamic facial geometry, captured using moderate to video rates of acquisition, for every captured frame.
Reference:
Temporal Upsampling of Performance Geometry using Photometric Alignment (Cyrus A. Wilson, Abhijeet Ghosh, Pieter Peers, Jen-Yuan Chiang, Jay Busch, Paul Debevec), In ACM Transactions on Graphics, volume 29, 2010.
Bibtex Entry:
@article{wilson_temporal_2010,
	title = {Temporal {Upsampling} of {Performance} {Geometry} using {Photometric} {Alignment}},
	volume = {29},
	url = {http://ict.usc.edu/pubs/Temporal%20Upsampling%20of%20Performance%20Geometry%20Using%20Photometric%20Alignment.pdf},
	abstract = {We present a novel technique for acquiring detailed facial geometry of a dynamic performance using extended spherical gradient illumination. Key to our method is a new algorithm for jointly aligning two photographs – under a gradient illumination condition and its complement – to a full-on tracking frame, providing dense temporal correspondences under changing lighting conditions. We employ a two step algorithm to reconstruct detailed geometry for every captured frame. In the first step, we coalesce information from the gradient illumination frames to the full-on tracking frame, and form a temporally aligned photometric normal map, which is subsequently combined with dense stereo correspondences yielding a detailed geometry. In a second step, we propagate the detailed geometry back to every captured instance guided by the previously computed dense correspondences. We demonstrate reconstructed dynamic facial geometry, captured using moderate to video rates of acquisition, for every captured frame.},
	number = {2},
	journal = {ACM Transactions on Graphics},
	author = {Wilson, Cyrus A. and Ghosh, Abhijeet and Peers, Pieter and Chiang, Jen-Yuan and Busch, Jay and Debevec, Paul},
	month = mar,
	year = {2010},
	keywords = {Graphics}
}
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