Automatic Failure Recovery and Re-Initialization for Online UAV Tracking with Joint Scale and Aspect Ratio Optimization


Current unmanned aerial vehicle (UAV) visual tracking algorithms are primarily limited with respect to”:” (i) the kind of size variation they can deal with, (ii) the implementation speed which hardly meet the real-time requirement. In this work, a real-time UAV tracking algorithm with powerful size estimation ability is proposed. Specifically, the overall tracking task is allocated to two 2D filters”:” (i) translation filter for location prediction in the space domain, (ii) size filter for scale and aspect ratio optimization in the size domain. Besides, an efficient two-stage re-detection strategy is introduced for long-term UAV tracking tasks. Large-scale experiments on four UAV benchmarks demonstrate the superiority of the presented method which has computation feasibility on a low-cost CPU.

In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, USA, pp.1-8, 2020.
Fangqiang Ding
PhD Candidate in Robotics and Autonomous System at Edin., U.K.