OBJECT LOCALIZATION FOR SUBSEQUENT UAV TRACKING
The paper is devoted to the problem of semi-automatic initialization of the tracking algorithm, i.e. selecting an object of interest by unmanned aerial vehicles or drones. In this work, we propose an algorithm to refine the position and dimensions of the boundary box of the tracked object at the initial time (on the first frame), based on saliency detection algorithm, which simulates the map of human attention. We tested existing algorithms for object tracking by UAVs on the largest and most complex dataset – UAV 123. It is shown that the quality of tracking as a result of initialization by the proposed algorithm varies within acceptable limits for successful tracking of the object. The advantage of the proposed approach is that it applies the principles, used by the human visual system: the color, contrast, central focus.