Vincente Guis

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Because photometric surveys of exoplanet transits are very promising sources of future discoveries, many algorithms are being developed to detect transit signals in stellar light curves. This paper compares such algorithms for the next generation of space-based transit detection surveys like CoRoT, Kepler, and Eddington. Five independent analyses of a(More)
In this paper, we propose a supervised object recognition method using new global features and inspired by the model of the human primary visual cortex V1 as the semidiscrete roto-translation group $$SE(2,N) = {\mathbb {Z}}_N\rtimes {\mathbb {R}}^2$$ S E ( 2 , N ) = Z N ⋊ R 2 . The proposed technique is based on generalized Fourier descriptors on the latter(More)
In this paper, an efficient unsupervised approach for extracting objects from maritime background using solely still video images is proposed. Its main idea is that maritime background (sea) has the main particularity of absorbing only hot light frequencies (red and green), while an object has not this property. Therefore if a timely vector of class(More)
This paper describes a novel approach for rigid object segmentation from a dynamic background using a pre-recorded video with a moving camera, and we apply it to the problem of vessel segmentation in a maritime video scene. The difficulty of modeling background appearance or/and dynamic, modeling object appearance, and compensating camera motion renders(More)
This article addresses the problem of near real time video analysis of a maritime scene using a (moving) airborne RGB video camera in the goal of detecting and eventually recognizing a target maritime vessel. This is a very challenging problem mainly due to the high level of uncertainty of a maritime scene including a dynamic and noisy background, camera's(More)
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