A Unified Approach for Tracking UAVs in Infrared

Abstract

With complex camera and object movement, the tracked object often suffers camera motion, out of view, dramatic scale variation, etc., which severely influence tracking performance. Due to the fast speed and tiny size of unmanned aerial vehicles(UAV), it is crucial to design a robust framework for tracking UAVs. This paper carefully designs a unified framework, including a local tracker, camera motion estimation module, bounding box refinement module, re-detection module and model updater. The camera motion estimation module achieves motion compensation for the local tracker. Then, the bounding box refinement module aims to measure an accurate bounding box. If the target is missing, we switch to the re-detection module to re-localize the target when it reappears. We also adopt a model updater to control the updating process and filter out unreliable samples. Numerous experimental results on 9 visual/thermal datasets show the effectiveness and generalization of our framework.