Georgios Papamakarios

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The robust estimation of the low-dimensional subspace that spans the data from a set of high-dimensional, possibly corrupted by gross errors and outliers observations is fundamental in many computer vision problems. The state-of-the-art robust principal component analysis (PCA) methods adopt convex relaxations of 0 quasi-norm-regularised rank minimisation(More)
This paper presents a tool to support and monitor the execution of common physical exercise interventions targeting people with Mild Cognitive Impairment (MCI), Alzheimer's disease (AD) and elderly in general. Our tool aims (a) to stimulate and guide patients within physical exercise programs , (b) to monitor patient capacity to perform exercises suggested(More)
This paper presents an acceleration method, using both algorithmic and architectural means, for fast calculation of local correlation coefficients, which is a basic image-based information processing step for template or pattern matching, image registration, motion or change detection and estimation, compensation of changes, or compression of(More)
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