Persistent Aerial Tracking
dc.contributor.advisor | Ghanem, Bernard | |
dc.contributor.author | Mueller, Matthias | |
dc.date.accessioned | 2016-05-08T11:15:55Z | |
dc.date.available | 2016-05-08T11:15:55Z | |
dc.date.issued | 2016-04-13 | |
dc.identifier.citation | Mueller, M. (2016). Persistent Aerial Tracking. KAUST Research Repository. https://doi.org/10.25781/KAUST-HWH6B | |
dc.identifier.doi | 10.25781/KAUST-HWH6B | |
dc.identifier.uri | http://hdl.handle.net/10754/608605 | |
dc.description.abstract | In this thesis, we propose a new aerial video dataset and benchmark for low altitude UAV target tracking, as well as, a photo-realistic UAV simulator that can be coupled with tracking methods. Our benchmark provides the first evaluation of many state of-the-art and popular trackers on 123 new and fully annotated HD video sequences captured from a low-altitude aerial perspective. Among the compared trackers, we determine which ones are the most suitable for UAV tracking both in terms of tracking accuracy and run-time. We also present a simulator that can be used to evaluate tracking algorithms in real-time scenarios before they are deployed on a UAV ”in the field”, as well as, generate synthetic but photo-realistic tracking datasets with free ground truth annotations to easily extend existing real-world datasets. Both the benchmark and simulator will be made publicly available to the vision community to further research in the area of object tracking from UAVs. Additionally, we propose a persistent, robust and autonomous object tracking system for unmanned aerial vehicles (UAVs) called Persistent Aerial Tracking (PAT). A computer vision and control strategy is applied to a diverse set of moving objects (e.g. humans, animals, cars, boats, etc.) integrating multiple UAVs with a stabilized RGB camera. A novel strategy is employed to successfully track objects over a long period, by ’handing over the camera’ from one UAV to another. We integrate the complete system into an off- 4 the-shelf UAV, and obtain promising results showing the robustness of our solution in real-world aerial scenarios. | |
dc.language.iso | en | |
dc.subject | object tracking | |
dc.subject | Aerial tracking | |
dc.subject | UAV | |
dc.subject | surveillance | |
dc.subject | Benchmark | |
dc.subject | Simulator | |
dc.title | Persistent Aerial Tracking | |
dc.type | Thesis | |
dc.contributor.department | Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division | |
thesis.degree.grantor | King Abdullah University of Science and Technology | |
dc.contributor.committeemember | Shamma, Jeff S. | |
dc.contributor.committeemember | Wonka, Peter | |
thesis.degree.discipline | Electrical and Computer Engineering | |
thesis.degree.name | Master of Science | |
refterms.dateFOA | 2018-06-13T12:22:57Z |
Files in this item
This item appears in the following Collection(s)
-
MS Theses
-
Electrical and Computer Engineering Program
For more information visit: https://cemse.kaust.edu.sa/ece -
Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
For more information visit: https://cemse.kaust.edu.sa/