Mutual segmentation with level sets

Tammy Riklin-Raviv; Nir Sochen; Nahum Kiryati

doi:10.1109/CVPRW.2006.142

Mutual segmentation with level sets

Tammy Riklin-Raviv^*, Nir Sochen, Nahum Kiryati

^*Corresponding author for this work

Tel Aviv University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	2006 Conference on Computer Vision and Pattern Recognition Workshop
DOIs	https://doi.org/10.1109/CVPRW.2006.142
State	Published - 2006
Event	2006 Conference on Computer Vision and Pattern Recognition Workshops - New York, NY, United States Duration: 17 Jun 2006 → 22 Jun 2006

Publication series

Name	Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume	2006
ISSN (Print)	1063-6919

Conference

Conference	2006 Conference on Computer Vision and Pattern Recognition Workshops
Country/Territory	United States
City	New York, NY
Period	17/06/06 → 22/06/06

Access to Document

10.1109/CVPRW.2006.142

Cite this

@inproceedings{325c2b09ed694e64a3b29c5c797b43fc,

title = "Mutual segmentation with level sets",

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.",

author = "Tammy Riklin-Raviv and Nir Sochen and Nahum Kiryati",

year = "2006",

doi = "10.1109/CVPRW.2006.142",

language = "אנגלית",

isbn = "0769526462",

series = "Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition",

booktitle = "2006 Conference on Computer Vision and Pattern Recognition Workshop",

note = "2006 Conference on Computer Vision and Pattern Recognition Workshops ; Conference date: 17-06-2006 Through 22-06-2006",

}

Riklin-Raviv, T, Sochen, N & Kiryati, N 2006, Mutual segmentation with level sets. in 2006 Conference on Computer Vision and Pattern Recognition Workshop., 1640625, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshops, New York, NY, United States, 17/06/06. https://doi.org/10.1109/CVPRW.2006.142

Mutual segmentation with level sets. / Riklin-Raviv, Tammy; Sochen, Nir ; Kiryati, Nahum.
2006 Conference on Computer Vision and Pattern Recognition Workshop. 2006. 1640625 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; Vol. 2006).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Mutual segmentation with level sets

AU - Riklin-Raviv, Tammy

AU - Sochen, Nir

AU - Kiryati, Nahum

PY - 2006

Y1 - 2006

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=33845532566&partnerID=8YFLogxK

U2 - 10.1109/CVPRW.2006.142

DO - 10.1109/CVPRW.2006.142

M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???

AN - SCOPUS:33845532566

SN - 0769526462

SN - 9780769526461

T3 - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

BT - 2006 Conference on Computer Vision and Pattern Recognition Workshop

T2 - 2006 Conference on Computer Vision and Pattern Recognition Workshops

Y2 - 17 June 2006 through 22 June 2006

ER -

Mutual segmentation with level sets

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this