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Our goal is to automatically recognize hand grasps and to discover the visual structures (relationships) between hand grasps using wearable cameras. Wearable cameras provide a first-person perspective which enables continuous visual hand grasp analysis of everyday activities. In contrast to previous work focused on manual analysis of first-person videos of hand grasps, we propose a fully automatic vision-based approach for grasp analysis. A set of grasp classifiers are trained fordoi:10.1109/icra.2015.7139367 dblp:conf/icra/CaiKS15 fatcat:ehjvyeozhzeqtpimegjhwmcuda