Statistics on manifolds and landmarks based image analysis: A nonparametric theory with applications

Rabi Bhattacharya, Vic Patrangenaru

Research output: Contribution to journalArticle

7 Scopus citations

Abstract

This paper provides an exposition of some recent developments in nonparametric inference on manifolds, along with a brief account of an emerging theory on data analysis on stratified spaces. Much of the theory is developed around the notion of Fréceht means with applications, for the most part, to landmark based shape spaces. A number of applications are illustrated with real data in such areas as paleomagnetism, morphometrics and medical diagnostics. Connections to scene recognition and machine vision are also explored.

Original languageEnglish (US)
Pages (from-to)1-22
Number of pages22
JournalJournal of Statistical Planning and Inference
Volume145
DOIs
StatePublished - Feb 1 2014

Keywords

  • Fre'chet mean
  • Nonparametric inference on manifolds Kendall's shape spaces
  • Projective shape spaces
  • Reflection similarity shape
  • Stratified spaces

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

Fingerprint Dive into the research topics of 'Statistics on manifolds and landmarks based image analysis: A nonparametric theory with applications'. Together they form a unique fingerprint.

  • Cite this