An Information Theoretic Approach to Statistical Shape Modelling

R H Davies, T F Cootes, C J Twining and C J Taylor

Statistical shape models have been used widely as a basis for segmenting and interpreting images. A major drawback of the approach is the need to establish a set of dense correspondences across a training set of segmented shapes. By posing the problem as one of minimising the description length of the model, we develop an efficient method that automatically defines correspondences across a set of shapes. Results are given for several different training sets of shapes, showing that the automatic method constructs significantly better models than those built by hand - the current gold standard.

PDF version

Home Contents Author index Keyword index

Valid CSS! Valid HTML 4.01!

This document produced for BMVC 2001