Gradient flows and geometric active contour models

Satyanad Kichenassamy, Arun Kumar, Peter Olver, Allen Tannenbaum, Anthony Yezzi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

492 Scopus citations

Abstract

In this paper, we analyze the geometric active contour models discussed in [6, 18] from a curve evolution point of view and propose some modifications based on gradient flows relative to certain new feature-based Riemannian metrics. This leads to a novel snake paradigm in which the feature of interest may be considered to lie at the bottom of a potential well. Thus the snake is attracted very naturally and efficiently to the desired feature. Moreover, we consider some 3-D active surface models based on these ideas.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Computer Vision
Editors Anon
PublisherIEEE
Pages810-815
Number of pages6
StatePublished - Jan 1 1995
EventProceedings of the 5th International Conference on Computer Vision - Cambridge, MA, USA
Duration: Jun 20 1995Jun 23 1995

Other

OtherProceedings of the 5th International Conference on Computer Vision
CityCambridge, MA, USA
Period6/20/956/23/95

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