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Facial Expression Modelling from Still Images Using a Single Generic 3D Head Model

  • Michael Hähnel
  • Andreas Wiratanaya
  • Karl-Friedrich Kraiss
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4174)

Abstract

We propose two approaches to facial expression modelling from single still images using a generic 3D head model without the need of large image databases (like e.g. Active Appearance Models). The first approach estimates the parameters of linear muscle models to obtain a biologically inspired model of the facial expression which may be changed intuitively afterwards. The second approach uses RBF-based interpolation to deform the head model according to the given expression. As a preprocessing stage for face recognition, this approach could achieve significantly higher recognition rates than in the un-normalized case based on the Eigenface approach, local binary patterns and a grey-scale correlation measure.

Keywords

Facial Expression Feature Point Face Recognition Face Image Local Binary Pattern 
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 Berlin Heidelberg 2006

Authors and Affiliations

  • Michael Hähnel
    • 1
  • Andreas Wiratanaya
    • 1
  • Karl-Friedrich Kraiss
    • 1
  1. 1.Institute of Man-Machine-InteractionRWTH Aachen UniversityGermany

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