Stochastic Shape Analysis

Alexis Arnaudon (), Darryl Holm and Stefan Sommer ()
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Alexis Arnaudon: Imperial College, Department of Mathematics
Darryl Holm: Imperial College, Department of Mathematics
Stefan Sommer: University of Copenhagen, Department of Computer Science (DIKU)

Chapter 38 in Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging, 2023, pp 1325-1348 from Springer

Abstract: Abstract The chapter describes stochastic models of shapes from a Hamiltonian viewpoint, including Langevin models, Riemannian Brownian motions and stochastic variational systems. Starting from the deterministic setting of outer metrics on shape spaces and transformation groups, we discuss recent approaches to introducing noise in shape analysis from a physical or Hamiltonian point of view. We furthermore outline important applications and statistical uses of stochastic shape models, and we discuss perspectives and current research efforts in stochastic shape analysis.

Keywords: Shape analysis; Stochastic geometric mechanics; Hamiltonian systems; Langevin equations; Stochastic Euler-Poincaré equations (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-98661-2_86

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DOI: 10.1007/978-3-030-98661-2_86

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