Abstract
Unmanned aerial vehicles (UAV) equipped with intelligent gimbaled cameras can take images and identify specific targets from them in real-time. However, the targets in the images are generally small and difficult to be seen. This paper proposes an Online Target Close-up Shooting (OTCS) method to solve the problem of taking high-definition (HD) close-up images of the targets. Firstly, we build an online target close-up shooting model, which uses deep learning (DL) algorithm to identify the targets from the images taken online. Then, an intelligent control algorithm is presented to control the gimbaled camera to take a close-up shot of the target, which considered the target being fixed on the ground statically and moving at an ununiform speed. Finally, we build a UAV-based prototype system and conduct a series of experiments to verify our proposal. Experimental results show that our proposed method is feasible and outperforms traditional methods in effectiveness.
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