Vincente Guis

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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 we propose a supervised object recognition method using new global features. The proposed technique, based on the Fourier transform of a regular hexagonal grid, allows extracting descriptors which are invariant to geometric transformations (rotations , scale invariant, translations...). The obtained descriptors are next used in order to feed(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)
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