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Inspired by the early visual system of many mammalians we consider the construction of-and reconstruction from-an orientation score U f : R 2 ×S 1 → C as a local orientation representation of an image, f : R 2 → R. The mapping f → U f is a wavelet transform W ψ corresponding to a reducible representation of the Euclidean motion group onto L 2 (R 2) and(More)
This paper describes a robust algorithm for estimation of local signal frequency and bandwidth. The method is based on combining local estimates of instantaneous frequency over a large number of scales. The filters used are a set of lognormal quadrature wavelets. A novel feature is that an estimate of local frequency bandwidth can be obtained. The bandwidth(More)
A new form of image estimator, which takes account of linear features, is derived using a signal equivalent formulation. The estimator is shown to be a nonstationary linear combination of three stationary estimators. The relation of the estimator to human visual physiology is discussed. A method for estimating the nonstationary control information is(More)
ii Abstract This thesis deals with focus of attention control in active vision systems. A framework for hierarchical gaze control in a robot vision system is presented , and an implementation for a simulated robot is described. The robot is equipped with a heterogeneously sampled imaging system, a fovea, resembling the spatially varying resolution of a(More)
This report brings together a novel approach to some computer vision problems and a particular algorithmic development of the Landweber iterative algorithm. The algorithm solves a class of high-dimensional, sparse, and constrained least-squares problems, which arise in various computer vision learning tasks, such as object recognition and object pose(More)
One major goal of the COSPAL project is to develop an artificial cognitive system architecture with the capability of exploratory learning. Exploratory learning is a strategy that allows to apply generalization on a conceptual level, resulting in an extension of competences. Whereas classical learning methods aim at best possible generalization, i.e.,(More)