Temporal Upsampling of Performance Geometry Using Photometric Alignment

ACM Transactions on Graphics, Volume 29, Issue 2 (March 2010) Presented at SIGGRAPH 2010

Cyrus A. Wilson   Abhijeet Ghosh   Pieter Peers   Jen-Yuan Chiang   Jay Busch   Paul Debevec

USC Institute for Creative Technologies

 

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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.

 

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Material:

ACM Transactions on Graphics Paper

• ACM TOG Paper
• ACM TOG Official Site

ACM Transactions on Graphics Video

• PhotometricAlignment_TOG_2010.mp4, 52.5 MB. ( Quicktime )
• PhotometricAlignment_TOG_2010.m4v (For iPhone) , 15 MB. ( Quicktime )

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Related Projects:

• Light Stage 5:
  • Rapid Acquisition of Specular and Diffuse Normal Maps from Polarized Spherical Gradient Illumination , EGSR 2007
  • Facial Performance Synthesis using Deformation-Driven Polynomial Displacement Maps , SIGGRAPH Asia 2008
  • High Resolution Face Scanning for "Digital Emily" , ICT & Image Metrics Collaboration