Robust statistics in shape fitting

A. Stein, M. Werman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

18 Scopus citations

Abstract

The concept of robustness in statistics is examined. Starting from the concepts of the breakdown point and equivariance properties of an estimator, the desired equivariance properties for shape fitting are defined, and high breakdown point methods with these properties are found.

Original languageEnglish
Title of host publicationProceedings CVPR 1992 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition
PublisherIEEE Computer Society
Pages540-546
Number of pages7
ISBN (Electronic)0818628553
DOIs
StatePublished - 1992
Event1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 1992 - Champaign, United States
Duration: 15 Jun 199218 Jun 1992

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume1992-June
ISSN (Print)1063-6919

Conference

Conference1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 1992
Country/TerritoryUnited States
CityChampaign
Period15/06/9218/06/92

Bibliographical note

Publisher Copyright:
© 1992 IEEE.

Fingerprint

Dive into the research topics of 'Robust statistics in shape fitting'. Together they form a unique fingerprint.

Cite this