Parametric and nonparametric inference for statistical dynamic shape analysis with applications [electronic resource] / Chiara Brombin, Luigi Salmaso, Lara Fontanella, Luigi Ippoliti, Caterina Fusilli.
Brombin, Chiara, author.; Salmaso, Luigi, author.; Fontanella, Lara, author.; Ippoliti, Luigi, author.; Fusilli, Caterina, author.
2016
QA276
Available Online

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Title Parametric and nonparametric inference for statistical dynamic shape analysis with applications [electronic resource] / Chiara Brombin, Luigi Salmaso, Lara Fontanella, Luigi Ippoliti, Caterina Fusilli.
Author Brombin, Chiara, author.
ISBN 9783319263113 (electronic book)
3319263110 (electronic book)
9783319263106
DOI https://doi.org/10.1007/978-3-319-26311-3
Published Cham : Springer, [2016]
Copyright ©2016
Language English
Description 1 online resource : illustrations.
Item Number 10.1007/978-3-319-26311-3 doi
Call Number QA276
Dewey Decimal Classification 519.5
Summary This book considers specific inferential issues arising from the analysis of dynamic shapes with the attempt to solve the problems at hand using probability models and nonparametric tests. The models are simple to understand and interpret and provide a useful tool to describe the global dynamics of the landmark configurations. However, because of the non-Euclidean nature of shape spaces, distributions in shape spaces are not straightforward to obtain. The book explores the use of the Gaussian distribution in the configuration space, with similarity transformations integrated out. Specifically, it works with the offset-normal shape distribution as a probability model for statistical inference on a sample of a temporal sequence of landmark configurations. This enables inference for Gaussian processes from configurations onto the shape space. The book is divided in two parts, with the first three chapters covering material on the offset-normal shape distribution, and the remaining chapters covering the theory of NonParametric Combination (NPC) tests. The chapters offer a collection of applications which are bound together by the theme of this book. They refer to the analysis of data from the FG-NET (Face and Gesture Recognition Research Network) database with facial expressions. For these data, it may be desirable to provide a description of the dynamics of the expressions, or testing whether there is a difference between the dynamics of two facial expressions or testing which of the landmarks are more informative in explaining the pattern of an expression.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (viewed February 16, 2016).
Added Author Salmaso, Luigi, author.
Fontanella, Lara, author.
Ippoliti, Luigi, author.
Fusilli, Caterina, author.
Series SpringerBriefs in statistics.
Available in Other Form Print version: 9783319263106
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Part I Offset Normal Distribution for Dynamic Shapes
Basic Concepts and Definitions
Shape Inference and the Offset-Normal Distribution
Dynamic Shape Analysis Through the Offset-Normal Distribution
Part II Combination-Based Permutation Tests for Shape Analysis
Parametric and Non-Parametric Testing of Mean Shapes
Applications of NPC Methodology
Shape Inference and the Offset-Normal Distribution. .

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