Abstract: In this work we present a probabilistic approach to find motion patterns in manipulative tasks by looking for similarities among the relevant features along of the actions phases of a trajectories dataset. From multiples observations of human movements we can align all signals temporally to perform a learning process based on selection of relevant features by analyzing their probability distribution and finding correspondent features with high probability in each phase of the trajectories of a dataset. Using the spatio-temporal information of t...
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