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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Auteur principal: Becker, Stefan (auth)
Format: Électronique Chapitre de livre
Langue:anglais
Publié: Karlsruhe KIT Scientific Publishing 2020
Collection:Karlsruher Schriften zur Anthropomatik
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