The Offset Normal Shape Distribution for Dynamic Shape Analysis

This article deals with the statistical analysis of landmark data observed at different temporal instants. Statistical analysis of dynamic shapes is a problem with significant challenges due to the difficulty in providing a description of the shape changes over time, across subjects and over groups...

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Bibliographic Details
Published inJournal of computational and graphical statistics Vol. 28; no. 2; pp. 374 - 385
Main Authors Fontanella, Lara, Ippoliti, Luigi, Kume, Alfred
Format Journal Article
LanguageEnglish
Published Alexandria Taylor & Francis 03.04.2019
American Statistical Association, the Institute of Mathematical Statistics, and the Interface Foundation of North America
Taylor & Francis Ltd
Subjects
EM algorithm
Offset-normal shape distribution
Shape analysis
Spatio-temporal correlations
Statistical analysis
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Summary:This article deals with the statistical analysis of landmark data observed at different temporal instants. Statistical analysis of dynamic shapes is a problem with significant challenges due to the difficulty in providing a description of the shape changes over time, across subjects and over groups of subjects. There are several modeling strategies, which can be used for dynamic shape analysis. Here, we use the exact distribution theory for the shape of planar correlated Gaussian configurations and derive the induced offset-normal shape distribution. Various properties of this distribution are investigated, and some special cases discussed. This work is a natural progression of what has been proposed in Mardia and Dryden, Dryden and Mardia, Mardia and Walder, and Kume and Welling. Supplemental materials for this article are available online.
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ISSN:1061-8600
1537-2715
DOI:10.1080/10618600.2018.1530118