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Point Distribution Models rely on [[Landmark point]]s. A landmark is an annotating point posed by an anatomist onto a given locus for every shape instance across the training set population. For instance, the same landmark will designate the tip of the index in a training set of 2D hands outlines. [[Principal Component Analysis]] (PCA), for instance, is a relevant tool for studying correlations of movement between groups of landmarks among the training set population. Typically, it might detect that all the landmarks located along the same finger move exactly together across the training set examples showing different finger spacing for a flat-posed hands collection.
The implementation of the procedure is
* '''1:''' annotate the training set outlines with enough corresponding landmarks to sufficiently approximate the geometry of the original shapes
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