  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 meets 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.
