Dynamic Switching State Systems for Visual Tracking
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https://library.oapen.org/bitstream/20.500.12657/46859/1/dynamic-switching-state-systems-for-visual-tracking.pdfAuthor(s)
Becker, Stefan
Language
EnglishAbstract
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 together.
Keywords
videobasierte Objektverfolgung; state estimation; visual tracking; trajectory prediction; Trajektorienpradiktion; ZustandsschatzungISBN
9783731510383Publisher
KIT Scientific PublishingPublisher website
http://www.ksp.kit.edu/Publication date and place
Karlsruhe, 2020Series
Karlsruher Schriften zur Anthropomatik,Classification
Computer science