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...
Tallennettuna:
| Päätekijä: | |
|---|---|
| Aineistotyyppi: | Elektroninen Kirjan osa |
| Kieli: | englanti |
| Julkaistu: |
Karlsruhe
KIT Scientific Publishing
2020
|
| Sarja: | Karlsruher Schriften zur Anthropomatik
|
| Aiheet: | |
| Linkit: | DOAB: download the publication DOAB: description of the publication |
| Tagit: |
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OAPEN Library: description of the publication
Dynamic Switching State Systems for Visual Tracking
Julkaistu 2020
OAPEN Library: download the publication
OAPEN Library: description of the publication
Elektroninen
Kirjan osa