Abstract | ||
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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. |
Year | DOI | Venue |
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2010 | 10.1145/1731047.1731055 | ACM Trans. Graph. |
Keywords | Field | DocType |
gradient illumination condition,photorealism,photometric alignment,gradient illumination frame,motion estimation,detailed geometry,3d face scanning,dynamic facial geometry,extended spherical gradient illumination,optical flow,performance geometry,dense stereo,dense temporal correspondence,full-on tracking frame,temporal upsampling,capture,detailed facial geometry,dense correspondence | Computer vision,Facial geometry,Photometry (optics),Artificial intelligence,Motion estimation,Upsampling,Optical flow,Mathematics | Journal |
Volume | Issue | ISSN |
29 | 2 | 0730-0301 |
Citations | PageRank | References |
31 | 1.54 | 17 |
Authors | ||
6 |
Name | Order | Citations | PageRank |
---|---|---|---|
Cyrus A. Wilson | 1 | 123 | 9.32 |
Abhijeet Ghosh | 2 | 772 | 58.87 |
Pieter Peers | 3 | 1109 | 55.34 |
Jen-Yuan Chiang | 4 | 57 | 3.98 |
Jay Busch | 5 | 283 | 23.06 |
Paul Debevec | 6 | 4955 | 449.10 |