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Groupwise Diffeomorphic Non-rigid Registration for Automatic Model Building

  • T. F. Cootes
  • S. Marsland
  • C. J. Twining
  • K. Smith
  • C. J. Taylor
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3024)

Abstract

We describe a framework for registering a group of images together using a set of non-linear diffeomorphic warps. The result of the groupwise registration is an implicit definition of dense correspondences between all of the images in a set, which can be used to construct statistical models of shape change across the set, avoiding the need for manual annotation of training images. We give examples on two datasets (brains and faces) and show the resulting models of shape and appearance variation. We show results of experiments demonstrating that the groupwise approach gives a more reliable correspondence than pairwise matching alone.

Keywords

Face Image Appearance Model Large Mode Active Appearance Model Image Registration Method 
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 2004

Authors and Affiliations

  • T. F. Cootes
    • 1
  • S. Marsland
    • 1
  • C. J. Twining
    • 1
  • K. Smith
    • 1
  • C. J. Taylor
    • 1
  1. 1.Department of Imaging Science and Biomedical EngineeringUniversity of ManchesterManchesterUK

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