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Face Identification by Fitting a 3D Morphable Model Using Linear Shape and Texture Error Functions

  • Sami Romdhani
  • Volker Blanz
  • Thomas Vetter
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2353)

Abstract

This paper presents a novel algorithm aiming at analysis and identification of faces viewed from different poses and illumination conditions. Face analysis from a single image is performed by recovering the shape and textures parameters of a 3D Morphable Model in an analysis-by-synthesis fashion. The shape parameters are computed from a shape error estimated by optical flow and the texture parameters are obtained from a texture error. The algorithm uses linear equations to recover the shape and texture parameters irrespective of pose and lighting conditions of the face image. Identification experiments are reported on more than 5000 images from the publicly available CMU-PIE database which includes faces viewed from 13 different poses and under 22 different illuminations. Extensive identification results are available on our web page for future comparison with novel algorithms.

Keywords

Input Image Face Image Texture Parameter Stochastic Gradient Descent Active Appearance Model 
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 2002

Authors and Affiliations

  • Sami Romdhani
    • 1
  • Volker Blanz
    • 1
  • Thomas Vetter
    • 1
  1. 1.Institut für InformatikUniversity of FreiburgFreiburgGermany

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