A temporal belief filter improving human action recognition in videos
Résumé
In the context of human action recognition in video sequences, a Temporal Belief Filter based on the Transferable Belief Model is proposed. It ensures a consistency in the temporal belief evolution. The filter is useful to cope with varying video quality and experiment conditions by smoothing belief on actions and solving conflict due to contradictory parameters. The proposed approach is validated on real video sequences with moving camera under several view angles.
Domaines
Multimédia [cs.MM]
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