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Weight, Sex, and Facial Expressions: On the Manipulation of Attributes in Generative 3D Face Models

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Advances in Visual Computing (ISVC 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5875))

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Abstract

Generative 3D Face Models are expressive models with applications in modelling and editing. They are learned from example faces, and offer a compact representation of the continuous space of faces. While they have proven to be useful as strong priors in face reconstruction they remain to be difficult to use in artistic editing tasks. We describe a way to navigate face space by changing meaningful parameters learned from the training data. This makes it possible to fix attributes such as height, weight, age, expression or ‘lack of sleep’ while letting the infinity of unfixed other attributes vary in a statistically meaningful way.

We propose an inverse approach based on learning the distribution of faces in attribute space. Given a set of target attributes we then find the face which has the target attributes with high probability, and is as similar as possible to the input face.

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Author information

Authors and Affiliations

  1. University of Basel,  

    Brian Amberg, Pascal Paysan & Thomas Vetter

Authors
  1. Brian Amberg
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  2. Pascal Paysan
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  3. Thomas Vetter
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Graduate School of Science and Engineering, Saitama University, 255 Shimo-Okubo, Sakura-ku, Saitama-shi, 338-8570, Saitama, Japan

    Yoshinori Kuno

  6. Institute for Infocomm Research, 21 Heng Mui Keng Terrace, P.O. Box, 119613, Singapore

    Junxian Wang

  7. Department of Computer Science & Information Engineering, Tamkang University, Tamsui, Taipei, Taiwan, R.O.C.

    Jun-Xuan Wang

  8. Microsoft Research, Redmond, WA, USA

    Junxian Wang

  9. Department of Informatics, Univ. of Zurich, Winterthurerstr. 190, P.O. Box, 8057, Zurich, Switzerland

    Renato Pajarola

  10. Lawrence Livermore National Laboratory, 94550, Livermore, CA, USA

    Peter Lindstrom

  11. University of Applied Sciences Bonn-Rhein-Sieg, 53754, Sankt Augustin, Germany

    André Hinkenjann

  12. Humana Inc., 40202, Louisville, KY, USA

    Miguel L. Encarnação

  13. SCI Institute & School of Computing, University of Utah, 84112, Salt Lake City, UT, USA

    Cláudio T. Silva

  14. Desert Research Institute, 89512, Reno, NV, USA

    Daniel Coming

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© 2009 Springer-Verlag Berlin Heidelberg

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Amberg, B., Paysan, P., Vetter, T. (2009). Weight, Sex, and Facial Expressions: On the Manipulation of Attributes in Generative 3D Face Models. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2009. Lecture Notes in Computer Science, vol 5875. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10331-5_81

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  • DOI: https://doi.org/10.1007/978-3-642-10331-5_81

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10330-8

  • Online ISBN: 978-3-642-10331-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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