Titlebook: Scale-Space and Morphology in Computer Vision; Third International Michael Kerckhove Conference proceedings 2001 Springer-Verlag Berlin He

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Using the Vector Distance Functions to Evolve Manifolds of Arbitrary Codimensionuses the vector that connects any point in space to its closest point on the object. It can deal with smooth manifolds with and without boundaries and with shapes of different dimensions. It can be used to evolve such objects according to a variety of motions, including mean curvature. If discontinu

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Computing Optic Flow by Scale-Space Integration of Normal Flow, by fitting the normal components of a local polynomial model of the optic flow to the normal flow. This fitting is based on an analytically solvable optimization problem, in which an integration scale-space over the normal flow field regularizes the solution. An automatic local scale selection mec

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Tracking of Multi-state Hand Models Using Particle Filtering and a Hierarchy of Multi-scale Image Fe. A scale-invariant dissimilarity measure is proposed for comparing scale-space features at different positions and scales. Based on this measure, the likelihood of hierarchical, parameterized models can be evaluated in such a way that maximization of the measure over different models and their para

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Bayesian Object Detection through Level Curves Selectiontion, the a . distribution should capture the knowledge about objects. Taking inspiration from [.], we design a prior density that penalizes the area of homogeneous parts in images. The detection problem is further formulated as the estimation of the set of curves that maximizes the posterior distri

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Total Variation Based Oversampling of Noisy Imagesodel for image oversampling, we show how to modify it in order to properly achieve our two goals. We discuss the modification both under a theoretical point of view (the analysis of the preservation of some structural elements) and the practical point of view of experimental results.We also describe