Stochastic Shape Analysis

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

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.
Original languageEnglish
Title of host publicationHandbook of Mathematical Models and Algorithms in Computer Vision and Imaging : Mathematical Imaging and Vision
EditorsKe Chen, Carola-Bibiane Schönlieb, Xue-Cheng Tai, Laurent Younces
Publication date2021
ISBN (Electronic)978-3-030-03009-4
Publication statusPublished - 2021
SeriesSpringer Reference

ID: 261374268