Dynamic Switching State Systems for Visual Tracking

This work addresses the problem of how to capture the dynamics of maneuvering objects for visual tracking. Towards this end, the perspective of recursive Bayesian filters and the perspective of deep learning approaches for state estimation are considered and their functional viewpoints are brought t...

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Bibliografiske detaljer
Hovedforfatter: Becker, Stefan (auth)
Format: Electronisk Book Chapter
Sprog:engelsk
Udgivet: Karlsruhe KIT Scientific Publishing 2020
Serier:Karlsruher Schriften zur Anthropomatik
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Online adgang:DOAB: download the publication
DOAB: description of the publication
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