BMVC92 pp 9-18 | Cite as

Training Models of Shape from Sets of Examples

  • T. F. Cootes
  • C. J. Taylor
  • D. H. Cooper
  • J. Graham


A method for building flexible shape models is presented in which a shape is represented by a set of labelled points. The technique determines the statistics of the points over a collection of example shapes. The mean positions of the points give an average shape and a number of modes of variation are determined describing the main ways in which the example shapes tend to deform from the average. In this way allowed variation in shape can be included in the model. The method produces a compact flexible ‘Point Distribution Model’ with a small number of linearly independent parameters, which can be used during image search. We demonstrate the application of the Point Distribution Model in describing two classes of shapes.


Image Search Active Contour Model Resistor Model Hand Shape Procrustes Analysis 
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 1992

Authors and Affiliations

  • T. F. Cootes
    • 1
  • C. J. Taylor
    • 1
  • D. H. Cooper
    • 1
  • J. Graham
    • 1
  1. 1.Department of Medical BiophysicsUniversity of ManchesterManchesterUK

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