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.
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| - 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. (en)
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| - 2008-06-01 00:00:00.000000 (xsd:date)
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| - 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. (en)
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| - Generalized Procrustes analysis (en)
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