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Titlebook: Computer Vision Systems; 12th International C Dimitrios Tzovaras,Dimitrios Giakoumis,Antonis Arg Conference proceedings 2019 Springer Natur

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Fabrication Laboratories (Fab Labs)es for image representation with a view to reduce the computational cost. In order to achieve this, a training process is performed, where a feature matching technique indicates the features’ repeatability with respect to scale. Votes are distributed into the database through a nearest neighbor meth
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https://doi.org/10.1007/978-1-4842-5494-3igation tasks. The proposed method leverages the processing of a single camera to identify the deepest area in the scene in order to provide a collision free heading command for the MAV. In the sequel and inspired by haze removal approaches, the proposed novel idea is structured around a single imag
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https://doi.org/10.1007/978-3-658-24832-1 be equipped with global path planners that ensure coverage and full exploration of the operational area as well as dynamic local planners that address local obstacle avoidance. The paper at hand proposes a local obstacle detection algorithm based on a fast stereo vision processing step, integrated
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The Decision to Delist from the Stock Markettribution of this paper is integrating simple, efficient and well-established methods in the computer vision community in a state of the art vision-based system for Micro Aerial Vehicle (MAV) navigation in dark tunnels. These methods include Otsu’s threshold and Moore-Neighborhood object tracing. Th
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https://doi.org/10.1007/978-3-7908-2612-8 logistics, to search and rescue, to planetary exploration. To achieve this, robots must be able to estimate the traversability of the terrain they are facing, in order to be able to plan a safe path through rugged terrain. In the work described here, we pursue the idea of fine-tuning a generic visu
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