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- W2099461434 abstract "This work investigates the use of semantic information to link ground level occupancy maps and aerial images. A ground level semantic map, which shows open ground and indicates the probability of cells being occupied by walls of buildings, is obtained by a mobile robot equipped with an omni-directional camera, GPS and a laser range finder. This semantic information is used for local and global segmentation of an aerial image. The result is a map where the semantic information has been extended beyond the range of the robot sensors and predicts where the mobile robot can find buildings and potentially driveable ground." @default.
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- W2099461434 date "2008-06-01" @default.
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- W2099461434 title "Fusion of aerial images and sensor data from a ground vehicle for improved semantic mapping" @default.
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