UAV Target Tracking By Detection via Deep Neural Networks

This paper introduces an Image Based Visual Servoing (IBVS) system to track a ground target from a flying UAV. We implement a tracking system via two deep neural networks; approaching network and chasing network. In the approaching network, the UAV-target relative distance is estimated through the tracked target state to drive the UAV to a desired distance. In the chasing network, the tracked target orientation is used in resolving the ambiguity between the UAV's yawing and lateral movements and aligning the UAV with the tracked target heading to ease the tracking task. The detection accuracy for both networks has been validated and a series of real flight data, which has been conducted on ground targets and persons showed the proposed system efficiency in target tracking and following.