Shared sets of data for/from iCub to train machine learning algorithms.
iCubWorld datasets are collections of images recording the visual experience of iCub while observing objects in its typical environment, a laboratory or an office. The acquisition setting is devised to allow a natural human-robot interaction, where a teacher verbally provides the label of the object of interest and shows it to the robot, by holding it in the hand; the iCub can either track the object while the teacher moves it, or take it in its hand.
Since 2013, we published four iCubWorld releases of increasing size, aimed at investigating complementary aspects of robotic visual recognition. These image collections allow for extensive analysis of the behaviour of recognition systems when trained in different conditions, offering a faithful and reproducible benchmark for the performance that we can expect from the real system.