Generalized procrustes analysis
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The Procrustes distance provides a metric to minimize in order to align a pair of shape instances annotated by Landmark points. The Generalized Procrustes Analysis (GPA) is a procedure applying the aforementioned Procrustes analysis method to align a population of shapes instead of only two shape instances.
GPA This is one of the methods achieving this goal, namely useful to build a Point Distribution Model or to undertake any shape study on the training set. The algorithm outline is the following:
- 1: choose a reference shape among the training set instances
- 2: align all other instances on current reference
- 3: compute the mean shape of the current training set
- 4: if the proscrustes distance between the mean shape and the reference is above a threshold, set reference to mean shape and continue to step 2.
[edit] References
- I.L. Dryden and K.V. Mardia (1998). Statistical Shape Analysis. John Wiley & Sons. ISBN 0471958166.
