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Joint space-time image sequence segmentation based on volume competition and level sets

9 years 12 months ago
Joint space-time image sequence segmentation based on volume competition and level sets
In this paper, we address the issue of joint space-time segmentation of image sequences. Typical approaches to such segmentation consider two image frames at a time, and perform tracking of individual segmentations across time. We propose to perform this segmentation jointly over multiple frames. This leads to a 3-D segmentation, i.e., search for a volume "carved out" by a moving object in the (3-D) image sequence domain. We pose the problem in Bayesian framework and use the MAP criterion. Under suitable structural and segmentation/motion models we convert MAP estimation to a functional minimization. The resulting problem can be viewed as volume competition, a 3-D generalization of region competition. We parameterize the unknown surface to be estimated, but rather than solving for it using an active-surface approach, we embed it into a higher-dimensional function and use the level-set methodology. We show experimental results for the simpler case of object motion against sti...
Mirko Ristivojevic, Janusz Konrad
Added 24 Oct 2009
Updated 24 Oct 2009
Type Conference
Year 2002
Where ICIP
Authors Mirko Ristivojevic, Janusz Konrad
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