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Face recognition using active appearance models

  • G. J. Edwards
  • T. F. Cootes
  • C. J. Taylor
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1407)

Abstract

We present a new framework for interpreting face images and image sequences using an Active Appearance Model (AAM). The AAM contains a statistical, photo-realistic model of the shape and grey-level appearance of faces. This paper demonstrates the use of the AAM's efficient iterative matching scheme for image interpretation. We use the AAM as a basis for face recognition, obtain good results for difficult images. We show how the AAM framework allows identity information to be decoupled from other variation, allowing evidence of identity to be integrated over a sequence. The AAM approach makes optimal use of the evidence from either a single image or image sequence. Since we derive a complete description of a given image our method can be used as the basis for a range of face image interpretation tasks.

Keywords

Face Recognition Face Image Gesture Recognition Human Observer 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 1998

Authors and Affiliations

  • G. J. Edwards
    • 1
  • T. F. Cootes
    • 1
  • C. J. Taylor
    • 1
  1. 1.Wolfson Image Analysis Unit, Department of Medical BiophysicsUniversity of ManchesterManchesterUK

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