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Near-instant capture of high-resolution facial geometry and reflectance

Published:31 July 2015Publication History

ABSTRACT

Modeling realistic human characters is frequently done using 3D recordings of the shape and appearance of real people, often across a set of different facial expressions to build blendshape facial models. Believable characters that cross the "Uncanny Valley" require high-quality geometry, texture maps, reflectance properties, and surface detail at the level of skin pores and fine wrinkles. Unfortunately, there has not yet been a technique for recording such datasets that is near-instantaneous and low-cost. While some facial capture techniques are instantaneous and inexpensive [Beeler et al. 2010], these do not generally provide lighting-independent texture maps, specular reflectance information, or high-resolution surface normal detail for relighting. In contrast, techniques which use multiple photographs from spherical lighting setups [Ghosh et al. 2011] do capture such reflectance properties, at the expense of longer capture times and complicated custom equipment.

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References

  1. Beeler, T., Bickel, B., Beardsley, P., Sumner, B., and Gross, M. 2010. High-quality single-shot capture of facial geometry. ACM Trans. Graph. 29 (July), 40:1--40:9. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Ghosh, A., Fyffe, G., Tunwattanapong, B., Busch, J., Yu, X., and Debevec, P. 2011. Multiview face capture using polarized spherical gradient illumination. ACM Trans. Graphics (Proc. SIGGRAPH Asia) 30, 6. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Near-instant capture of high-resolution facial geometry and reflectance

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      • Published in

        cover image ACM Conferences
        SIGGRAPH '15: ACM SIGGRAPH 2015 Talks
        July 2015
        82 pages
        ISBN:9781450336369
        DOI:10.1145/2775280

        Copyright © 2015 Owner/Author

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 31 July 2015

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        Overall Acceptance Rate 1,553 of 7,229 submissions, 21%

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