Mutual segmentation with level sets

Tammy Riklin-Raviv, Nir Sochen, Nahum Kiryati

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

6 Scopus citations

Abstract

We suggest a novel variational approach for mutual segmentation of two images of the same object. The images are taken from different views, related by projective transformation. Each of the two images may not provide sufficient information for correct object-background delineation. The emerging segmentation of the object in each view provides a dynamic prior for the segmentation of the other image. The foundation of the proposed method is a unified level-set framework for region and edge based segmentation, associated with a shape similarity term. The dissimilarity between the two shape representations accounts for excess or deficient parts and is invariant to planar projective transformation. The suggested algorithm extracts the object in both images, correctly recovers its boundaries, and determines the homography between the two object views.

Original languageEnglish
Title of host publication2006 Conference on Computer Vision and Pattern Recognition Workshop
DOIs
StatePublished - 21 Dec 2006
Externally publishedYes
Event2006 Conference on Computer Vision and Pattern Recognition Workshops - New York, NY, United States
Duration: 17 Jun 200622 Jun 2006

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume2006
ISSN (Print)1063-6919

Conference

Conference2006 Conference on Computer Vision and Pattern Recognition Workshops
Country/TerritoryUnited States
CityNew York, NY
Period17/06/0622/06/06

Cite this