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IJCV
2006

Stochastic Motion and the Level Set Method in Computer Vision: Stochastic Active Contours

9 years 1 months ago
Stochastic Motion and the Level Set Method in Computer Vision: Stochastic Active Contours
Based on recent work on Stochastic Partial Differential Equations (SPDEs), this paper presents a simple and well-founded method to implement the stochastic evolution of a curve. First, we explain why great care should be taken when considering such an evolution in a Level Set framework. To guarantee the well-posedness of the evolution and to make it independent of the implicit representation of the initial curve, a Stratonovich differential has to be introduced. To implement this differential, a standard Ito plus drift approximation is proposed to turn an implicit scheme into an explicit one. Subsequently, we consider shape optimization techniques, which are a common framework to address various applications in Computer Vision, like segmentation, tracking, stereo vision etc. The objective
Olivier Juan, Renaud Keriven, Gheorghe Postelnicu
Added 12 Dec 2010
Updated 12 Dec 2010
Type Journal
Year 2006
Where IJCV
Authors Olivier Juan, Renaud Keriven, Gheorghe Postelnicu
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