Julien Rabin

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Visual evoked potentials (VEPs) were measured for sinusoidal gratings with spatio-chromatic modulation defined in a three-dimensional color space. The spatio-chromatic modulation of the gratings can be decomposed into contributions from an achromatic luminance varying component, an isoluminant component which modulates only the activities of L cones and M(More)
This paper proposes a new definition of the averaging of discrete probability distributions as a barycenter over theWasserstein space. Replacing the Wasserstein original metric by a sliced approximation over 1D distributions allows us to use a fast stochastic gradient descent algorithm. This new notion of barycenter of probabilities is likely to find(More)
Visual evoked potentials were recorded in response to spatiochromatic stimuli modulated in different directions in cone-activation color space from subjects with congenital and acquired color defects. This technique was effective for detection and classification of both mild and severe forms of congenital deficits. Results suggest that the visual evoked(More)
This article details two approaches to compute barycenters of measures using 1-D Wasserstein distances along radial projections of the input measures. The first method makes use of the Radon transform of the measures, and the second is the solution of a convex optimization problem over the space of measures. We show several properties of these barycenters(More)
This paper addresses the problem of recognizing multiple rigid objects that are common to two images. We propose a generic algorithm that allows to simultaneously decide if one or several objects are common to the two images and to estimate the corresponding geometric transformations. The considered transformations include similarities, homographies and(More)
This paper studies the problem of color transfer between images using optimal transport techniques. While being a generic framework to handle statistics properly, it is also known to be sensitive to noise and outliers, and is not suitable for direct application to images without additional postprocessing regularization to remove artifacts. To tackle these(More)
This work is concerned with the modification of the gray level or color distribution of digital images. A common drawback of classical methods aiming at such modifications is the revealing of artefacts or the attenuation of details and textures. In this work, we propose a generic filtering method enabling, given the original image and the radiometrically(More)
Many computer vision algorithms make use of local features, and rely on a systematic comparison of these features. The chosen dissimilarity measure is of crucial importance for the overall performances of these algorithms and has to be both robust and computationally efficient. Some of the most popular local features (like SIFT [4] descriptors) are based on(More)
This paper is devoted to the study of the Monge-Kantorovich theory of optimal mass transport, in the special case of one-dimensional and circular distributions. More precisely, we study the Monge-Kantorovich problem between discrete distributions on the unit circle S 1, in the case where the ground distance between two points x and y is defined as(More)