A geometrical derivation of the shape density
- 1 September 1991
- journal article
- Published by Cambridge University Press (CUP) in Advances in Applied Probability
- Vol. 23 (3) , 496-514
- https://doi.org/10.2307/1427619
Abstract
The density for the shapes of random configurations ofNindependent 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 coordinatesfor 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
This publication has 12 references indexed in Scilit:
- General shape distributions in a planeAdvances in Applied Probability, 1991
- The statistical analysis of shape dataBiometrika, 1989
- A Survey of the Statistical Theory of ShapeStatistical Science, 1989
- [A Survey of the Statistical Theory of Shape]: Comment: Some Contributions to Shape AnalysisStatistical Science, 1989
- Shape distributions for landmark dataAdvances in Applied Probability, 1989
- Techniques of Shape Analysis on Sets of PointsInternational Statistical Review, 1988
- Size and Shape Spaces for Landmark Data in Two DimensionsStatistical Science, 1986
- Quantitative Analysis of Surface GrowthBotanical Gazette, 1986
- A statistical method for biological shape comparisonsJournal of Theoretical Biology, 1984
- Shape Manifolds, Procrustean Metrics, and Complex Projective SpacesBulletin of the London Mathematical Society, 1984