k-Means Algorithm in Statistical Shape Analysis

DOI10.1080/03610911003765777zbMath1192.62160OpenAlexW2005832701MaRDI QIDQ3578980

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Publication date: 5 August 2010

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610911003765777

zbMATH Keywords

landmarksgeodesic distancenon-Euclidean spaces

Mathematics Subject Classification ID

Multivariate analysis (62H99) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to environmental and related topics (62P12)

Related Items (4)

The \(k\)-means algorithm for 3D shapes with an application to apparel design ⋮ Alpha geodesic distances for clustering of shapes ⋮ On clustering shape data ⋮ Bayesian Inference on Local Distributions of Functions and Multidimensional Curves with Spherical HMC Sampling

Uses Software

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Cites Work

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• Algorithm AS 136: A K-Means Clustering Algorithm
• Generalized Procrustes analysis
• The statistical theory of shape
• Shape Manifolds, Procrustean Metrics, and Complex Projective Spaces
• Mean Figures and Mean Shapes Applied to Biological Figure and Shape Distributions in the Plane
• Pivotal Bootstrap Methods fork-Sample Problems in Directional Statistics and Shape Analysis
• The elements of statistical learning. Data mining, inference, and prediction

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