TY - GEN
T1 - A Benchmark and Simulator for UAV Tracking
AU - Mueller, Matthias
AU - Smith, Neil
AU - Ghanem, Bernard
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: Research in this paper was supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research.
PY - 2016/9/17
Y1 - 2016/9/17
N2 - In this paper, we propose a new aerial video dataset and benchmark for low altitude UAV target tracking, as well as, a photorealistic 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. The simulator 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 automatic ground truth annotations to easily extend existing real-world datasets. Both the benchmark and simulator are made publicly available to the vision community on our website to further research in the area of object tracking from UAVs. (https://ivul.kaust.edu.sa/Pages/pub-benchmark-simulator-uav.aspx.). © Springer International Publishing AG 2016.
AB - In this paper, we propose a new aerial video dataset and benchmark for low altitude UAV target tracking, as well as, a photorealistic 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. The simulator 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 automatic ground truth annotations to easily extend existing real-world datasets. Both the benchmark and simulator are made publicly available to the vision community on our website to further research in the area of object tracking from UAVs. (https://ivul.kaust.edu.sa/Pages/pub-benchmark-simulator-uav.aspx.). © Springer International Publishing AG 2016.
UR - http://hdl.handle.net/10754/622126
UR - http://link.springer.com/chapter/10.1007%2F978-3-319-46448-0_27
UR - http://www.scopus.com/inward/record.url?scp=84990050293&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-46448-0_27
DO - 10.1007/978-3-319-46448-0_27
M3 - Conference contribution
SN - 9783319464473
SP - 445
EP - 461
BT - Lecture Notes in Computer Science
PB - Springer Nature
ER -