Abstract:Recent advances in tracking sensors and pose estimation software enable smart systems to use trajectories of skeleton joint locations for supervised learning. We study the problem of accurately recognizing sign language words, which is key to narrowing the communication gap between hard and non-hard of hearing people. Our method explores a geometric feature space that we call 'sub-skeleton' aspects of movement. We assess similarity of feature space trajectories using natural, speed invariant distance measures,… Show more
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