Multi-Object Tracking in Drone Videos
Abstract (englisch):
In this report, three popular methods for multi-pedestrian tracking are extended to a multi-category setting and tested on a large drone-based dataset. A thorough comparison of the algorithms is presented and a common shortcoming is identified. Building on this, a new tracking-by-detection based approach is developed that outperforms the other methods by a large margin. In addition, a state-of-the-art object detection model is adapted for the drone imagery, since no public detections are available for the dataset.
| Zugehörige Institution(en) am KIT | Institut für Anthropomatik und Robotik (IAR) |
| Publikationstyp | Proceedingsbeitrag |
| Publikationsjahr | 2021 |
| Sprache | Englisch |
| Identifikator | ISBN: 978-3-7315-1091-8 KITopen-ID: 1000135221 |
| Erschienen in | Proceedings of the 2020 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory. Ed.: J. Beyerer; T. Zander |
| Verlag | KIT Scientific Publishing |
| Seiten | 123-133 |
| Serie | Karlsruher Schriften zur Anthropomatik / Lehrstuhl für Interaktive Echtzeitsysteme, Karlsruher Institut für Technologie ; Fraunhofer-Inst. für Optronik, Systemtechnik und Bildauswertung IOSB Karlsruhe ; 51 |
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