Martial Sanfourche

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This paper focuses on applications of fuzzy segmentation in region indexing and image retrieval. First, our algorithm of fuzzy segmentation is shortly explained. Some features characterizing a fuzzy region are then defined, and a distance between fuzzy regions is proposed. This distance can be used to rank regions on color and/or shape features or to(More)
— We propose solutions to provide unmanned aerial vehicles (UAV) with features to understand the scene below and help the operational planning. First, using a visual mapping of the environnement, interactive learning of specific targets of interest is performed on the ground control station to build semantic maps useful for planning. Then, the learned(More)
This paper addresses the problem of absolute visual ego-localization of an autonomous vehicle equipped with a monocular camera that has to navigate in an urban environment. The proposed method is based on a combination of: 1) a Hidden Markov Model (HMM) exploiting the spatio-temporal coherency of acquired images and 2) learnt metrics dedicated to robust(More)
This paper presents an exemplar based metric learning framework dedicated to robust visual localization in complex scenes, e.g. street images. The proposed framework learns off-line a specific (local) metric for each image of the database, so that the distance between a database image and a query image representing the same scene is smaller than the(More)