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Dynamic Switching State Systems for Visual Tracking
Stefan Becker
2020
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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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Keywords
- Computer science
- Computing & information technology
- state estimation
- thema EDItEUR::U Computing and Information Technology::UY Computer science
- Trajectory Prediction
- Trajektorienprädiktion
- videobasierte Objektverfolgung
- visual tracking
- Zustandsschätzung
Links
DOI: 10.5445/KSP/1000122541Editions