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In this paper we address the problem of border detection for textured images by exploiting the concept of Bayesian complexity minimization as a generalization of the MDL paradigm in the Bayesian context. We aim at determining if a small window at a certain location corresponds to a single or several texture classes, which here are modeled as Gaussian Markov Random Fields (GMRF), thereby detecting...
A motion texture is the instantaneous scalar map of apparent motion values extracted from a dynamic or temporal texture. It is mostly displayed by natural scene elements (fire, smoke, water) but also involves more general textured motion patterns (eg. a crowd of people, a flock). In this work we are interested in the modeling and tracking of motion textures. Experimentally we observe that such motion...
Dynamic textures are time-varying visual patterns that exhibit certain spatio-temporal stationarity properties and are displayed mostly by natural scene elements. In this paper, we present new statistical models for the characterization of motion in this type of sequences. First we observe that motion measurements present values of two types: a discrete component at zero expressing the absence of...
The aim of this work is to model the apparent motion in image sequences depicting natural dynamic scenes. We adopt the mixed-state Markov random fields (MRF) models recently introduced to represent so-called motion textures. The approach consists in describing the spatial distribution of some motion measurements which exhibit mixed-state nature: a discrete component related to the absence of motion...
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