Variational Segmentation of Image Sequences Using Region-Based Active Contours and Deformable Shape Priors

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Variational Segmentation of Image Sequences Using Region-Based Active Contours and Deformable Shape Priors

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Publication Article, peer reviewed scientific
Title Variational Segmentation of Image Sequences Using Region-Based Active Contours and Deformable Shape Priors
Author(s) Fundana, Ketut ; Overgaard, Niels C ; Heyden, Anders
Date 2008
English abstract
In this paper we address the problem of segmentation in image sequences using region-based active contours and level set methods. We propose a novel method for variational segmentation of image sequences containing nonrigid, moving objects. The method is based on the classical Chan-Vese model augmented with a novel frame-to-frame interaction term, which allow us to update the segmentation result from one image frame to the next using the previous segmentation result as a shape prior. The interaction term is constructed to be pose-invariant and to allow moderate deformations in shape. It is expected to handle the appearance of occlusions which otherwise can make segmentation fail. The performance of the model is illustrated with experiments on synthetic and real image sequences.
DOI http://dx.doi.org/10.1007/s11263-008-0160-6 (link to publisher's fulltext)
Publisher Springer Kluwer Academic Publishers
Host/Issue International Journal of Computer Vision;3
Volume 80
ISSN 0920-5691
Pages 289-299
Language eng (iso)
Subject(s) Technology
Research Subject Categories::TECHNOLOGY
Research Subject Categories::MATHEMATICS
Handle http://hdl.handle.net/2043/10364 (link to this page)

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