Statistical Shape Analysis
by Kanti V. Mardia, Ian L. Dryden
Statistical Shape Analysis, 2nd Edition
- Preface
- Preface to the first edition
- Acknowledgements for the first edition
- 1 Introduction
- 2 Size measures and shape coordinates
- 3 Manifolds, shape and size-and-shape
- 4 Shape space
- 5 Size-and-shape space
- 6 Manifold means
- 7 Procrustes analysis
- 7.1 Introduction
- 7.2 Ordinary Procrustes analysis
- 7.3 Generalized Procrustes analysis
- 7.4 Generalized Procrustes algorithms for shape analysis
- 7.5 Generalized Procrustes algorithms for size-and-shape analysis
- 7.6 Variants of generalized Procrustes analysis
- 7.7 Shape variability: principal component analysis
- 7.8 Principal component analysis for size-and-shape
- 7.9 Canonical variate analysis
- 7.10 Discriminant analysis
- 7.11 Independent component analysis
- 7.12 Bilateral symmetry
- 8 2D Procrustes analysis using complex arithmetic
- 9 Tangent space inference
- 10 Shape and size-and-shape distributions
- 10.1 The uniform distribution
- 10.2 Complex Bingham distribution
- 10.3 Complex Watson distribution
- 10.4 Complex angular central Gaussian distribution
- 10.5 Complex Bingham quartic distribution
- 10.6 A rotationally symmetric shape family
- 10.7 Other distributions
- 10.8 Bayesian inference
- 10.9 Size-and-shape distributions
- 10.10 Size-and-shape versus shape
- 11 Offset normal shape distributions
- 12 Deformations for size and shape change
- 13 Non-parametric inference and regression
- 14 Unlabelled size-and-shape and shape analysis
- 15 Euclidean methods
- 16 Curves, surfaces and volumes
- 17 Shape in images
- 18 Object data and manifolds
- Exercises
- Appendix
- References
- Index
- WILEY SERIES IN PROBABILITY AND STATISTICS
- EULA
Statistical Shape Analysis
with Applications in R
Second Edition
Ian L. Dryden
The University of Nottingham, UK
Kanti V. Mardia
University of Leeds and University of Oxford, UK
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