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The dataset is composed of a set of 30 manually-annotated images with a 640x480 resolution. Frames were acquired by a Bumblebee2 stereo rig sensor, which is mounted on the forepart of the iCab research platform. Four different classes are used for labelling the dataset. The labelled categories correspond to the most popular instances found around the university campus and compose the minimum set required for in-campus navigation. The categories are: Traversable area (blue: RGB(0, 0, 255)) Garden (green: RGB(0, 255, 0)) Obstacles (red: RGB(255, 0, 0)) Pedestrian (yellow: RGB(255, 246, 0))
Campus Environment, semantic labelling, computer vision
Campus Environment, semantic labelling, computer vision
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