Mardia, KV, Fallaize, CJ, Barber, S et al. (2 more authors) (2013) Bayesian alignment of similarity shapes. Annals of Applied Statistics, 7 (2). 989 - 1009. ISSN 1932-6157
Abstract
We develop a Bayesian model for the alignment of two point configurations under the full similarity transformations of rotation, translation and scaling. Other work in this area has concentrated on rigid body transformations, where scale information is preserved, motivated by problems involving molecular data; this is known as form analysis.We concentrate on a Bayesian formulation for statistical shape analysis.We generalize the model introduced by Green and Mardia [Biometrika 93 (2006) 235-254] for the pairwise alignment of two unlabeled configurations to full similarity transformations by introducing a scaling factor to the model. The generalization is not straightforward, since the model needs to be reformulated to give good performance when scaling is included. We illustrate our method on the alignment of rat growth profiles and a novel application to the alignment of protein domains. Here, scaling is applied to secondary structure elements when comparing protein folds; additionally, we find that one global scaling factor is not in general sufficient to model these data and, hence, we develop a model in which multiple scale factors can be included to handle different scalings of shape components.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2013, Institute of Mathematical Studies. Reproduced in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 15 Jul 2013 09:39 |
Last Modified: | 15 Aug 2017 23:53 |
Published Version: | http://dx.doi.org/10.1214/12-AOAS615 |
Status: | Published |
Publisher: | Institute of Mathematical Studies |
Refereed: | Yes |
Identification Number: | 10.1214/12-AOAS615 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:75979 |