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The characteristic (or intrinsic) scale of a local image pattern is the scale parameter at which the Laplacian provides a local maximum. Nearly every position in an image will exhibit a small number of such characteristic scales. Computing a Gaussian jet at a characteristic scale provides a scale invariant feature vector for tracking, matching, indexing and(More)
In this article, we describe a module for the identification of brand logos from video data. A model for the visual appearance of each logo is generated from a small number of sample images using multidimensional histograms of scale-normalized chromatic Gaussian receptive fields. We compare several identification techniques based on multidimensional(More)
The characteristic (or intrinsic) scale of a local image pattern is the scale parameter at which the Laplacian provides a local maximum. Nearly every position in an image will exhibit a small number of such characteristic scales. Computing a vector of Gaussian derivatives (a Gaussian jet) at a characteristic scale provides a scale invariant feature vector(More)
Parallel MRI leads to magnitude data corrupted by noise described in most cases as following a Rician or a non central chi distribution. And yet, very few correction methods perform a non central chi noise removal. However, this correction step, adapted to the correct noise model, is of very much importance, especially when working with Diffusion Weighted(More)
Steerable video projection systems make it possible to use any convenient surface as a display. This paper describes a steerable projection system in which a projector and camera are mounted in an overhead motorized assembly with two degrees of freedom. Associating a remote camera to the video projector makes it possible to discover planar surfaces in the(More)
Parallel magnetic resonance imaging (MRI) yields noisy magnitude data, described in most cases as following a noncentral χ distribution when the signals received by the coils are combined as the sum of their squares. One well-known case of this noncentral χ noise model is the Rician model, but it is only valid in the case of single-channel acquisition.(More)
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