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A geometrical derivation of the shape density

Published online by Cambridge University Press:  01 July 2016

Colin R. Goodall  and
Kanti V. Mardia
Colin R. Goodall*
Affiliation:
Princeton University
Kanti V. Mardia*
Affiliation:
Leeds University
*
∗Postal address: Department of Civil Engineering and Operations Research, School of Engineering and Applied Science, Princeton University, Princeton, NJ 08544, USA.
∗∗Postal address: Department of Statistics, School of Mathematics, University of Leeds, Leeds LS2 9JT, UK.
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Abstract

The density for the shapes of random configurations of N independent Gaussian-distributed landmarks in the plane with unequal means was first derived by Mardia and Dryden (1989a). Kendall (1984), (1989) describes a hierarchy of spaces for landmarks, including Euclidean figure space containing the original configuration, preform space (with location removed), preshape space (with location and scale removed), and shape space. We derive the joint density of the landmark points in each of these intermediate spaces, culminating in confirmation of the Mardia–Dryden result in shape space. This three-step derivation is an appealing alternative to the single-step original derivation, and also provides strong geometrical motivation and insight into Kendall's hierarchy. Preform space and preshape space are respectively Euclidean space with dimension 2(N–1) and the sphere in that space, and thus the first two steps are reasonably familiar. The third step, from preshape space to shape space, is more interesting. The quotient by the rotation group partitions the preshape sphere into equivalence classes of preshapes with the same shape. We introduce a canonical system of preshape coordinates that include 2(N–2) polar coordinates for shape and one coordinate for rotation. Integration over the rotation coordinate gives the Mardia–Dryden result. However, the usual geometrical intuition fails because the set of preshapes keeping the rotation coordinate (however chosen) fixed is not an integrable manifold. We characterize the geometry of the quotient operation through the relationships between distances in preshape space and distances among the corresponding shapes.

Keywords

SIZE-AND-SHAPEPRESHAPELANDMARKSOFFSET NORMALREPEATED NORMAL INTEGRALRIEMANNIAN SUBMERSION
Type
Research Article
Information
Advances in Applied Probability , Volume 23 , Issue 3 , September 1991 , pp. 496 - 514
Copyright
Copyright © Applied Probability Trust 1991 

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