Gradient flows and geometric active contour models

I
ICCV
1995
Fifth International Conference on Computer Vision (ICCV'95)
Abstract - Gradient flows and geometric active contour models

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Fifth International Conference on Computer Vision (ICCV'95)

Massachusetts Institute of Technology, Cambridge, Massachusetts

June 20-June 23

ISBN: 0-8186-7042-8

	ASCII Text	x
	S. Kichenassamy, A. Kumar, P. Olver, A. Tannenbaum, A. Yezzi, "Gradient flows and geometric active contour models," Computer Vision, IEEE International Conference on, pp. 810, Fifth International Conference on Computer Vision (ICCV'95), 1995.

	BibTex	x
	@article{ 10.1109/ICCV.1995.466855, author = {S. Kichenassamy and A. Kumar and P. Olver and A. Tannenbaum and A. Yezzi}, title = {Gradient flows and geometric active contour models}, journal ={Computer Vision, IEEE International Conference on}, volume = {0}, year = {1995}, isbn = {0-8186-7042-8}, pages = {810}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICCV.1995.466855}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Computer Vision, IEEE International Conference on TI - Gradient flows and geometric active contour models SN - 0-8186-7042-8 SP EP A1 - S. Kichenassamy, A1 - A. Kumar, A1 - P. Olver, A1 - A. Tannenbaum, A1 - A. Yezzi, PY - 1995 KW - computer vision; computational geometry; gradient flows; geometric active contour models; curve evolution; feature-based Riemannian metrics; snake paradigm; 3-D active surface models VL - 0 JA - Computer Vision, IEEE International Conference on ER -

S. Kichenassamy, Dept. of Math., Minnesota Univ., Minneapolis, MN, USA

A. Kumar, Dept. of Math., Minnesota Univ., Minneapolis, MN, USA

P. Olver, Dept. of Math., Minnesota Univ., Minneapolis, MN, USA

A. Tannenbaum, Dept. of Math., Minnesota Univ., Minneapolis, MN, USA

A. Yezzi, Dept. of Math., Minnesota Univ., Minneapolis, MN, USA

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICCV.1995.466855

In this paper, we analyze the geometric active contour models discussed previously 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.

Index Terms:

computer vision; computational geometry; gradient flows; geometric active contour models; curve evolution; feature-based Riemannian metrics; snake paradigm; 3-D active surface models

Citation:

S. Kichenassamy, A. Kumar, P. Olver, A. Tannenbaum, A. Yezzi, "Gradient flows and geometric active contour models," iccv, pp.810, Fifth International Conference on Computer Vision (ICCV'95), 1995

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