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Morphable Models of Faces

  • Reinhard Knothe
  • Brian Amberg
  • Sami Romdhani
  • Volker Blanz
  • Thomas Vetter

Abstract

In this chapter, we present the Morphable Model, a three-dimensional (3D) representation that enables the accurate modeling of any illumination and pose as well as the separation of these variations from the rest (identity and expression). The Morphable Model is a generative model consisting of a linear 3D shape and appearance model plus an imaging model, which maps the 3D surface onto an image. The 3D shape and appearance are modeled by taking linear combinations of a training set of example faces. We show that linear combinations yield a realistic face only if the set of example faces is in correspondence. A good generative model should accurately distinguish faces from non faces. This is encoded in the probability distribution over the model parameters, which assigns a high probability to faces and a low probability to non faces. The distribution is learned together with the shape and appearance space from the training data.

Keywords

Face Recognition Input Image Face Image False Alarm Rate Face Recognition System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  • Reinhard Knothe
    • 1
  • Brian Amberg
    • 1
  • Sami Romdhani
    • 1
  • Volker Blanz
    • 2
  • Thomas Vetter
    • 1
  1. 1.Department of Mathematics and Computer ScienceUniversity of BaselBaselSwitzerland
  2. 2.Universität SiegenSiegenGermany

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