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...
| Other Authors: | |
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| Format: | eBook |
| Language: | Inglés |
| Published: |
Karlsruhe :
KIT Scientific Publishing
2020.
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| Series: | Karlsruher Schriften zur Anthropomatik
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| Subjects: | |
| See on Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009871124506719 |
| Summary: | 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. |
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| Physical Description: | 1 online resource (228 pages) : illustrations |
