Probabilistic Generative Modelling

  • Rasmus Larsen
  • Klaus Baggesen Hilger
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2749)

Abstract

The contribution of this paper is the adaption of data driven methods for decomposition of tangent shape variability proposed in a probabilistic framework. By Bayesian model selection we compare two generative model representations derived by principal components analysis and by maximum autocorrelation factors analysis.

Keywords

Principal Component Analysis Independent Component Analysis Active Appearance Model Bayesian Model Selection Medical Image Computing 
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 2003

Authors and Affiliations

  • Rasmus Larsen
    • 1
  • Klaus Baggesen Hilger
    • 1
  1. 1.Informatics and Mathematical ModellingTechnical University of DenmarkKgs. LyngbyDenmark

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