OTCS: An Online Target Close-Up Shooting Method Based on the UAV Image System

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 sol...

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Bibliographic Details
Published in:Wireless communications and mobile computing 2022-05, Vol.2022, p.1-10
Main Authors: Wang, Wentao, Wang, Huibin, Shi, Xuzhou, Chen, Ming
Format: Article
Language:English
Subjects:
Aerial photography
Algorithms
Border patrol
Cameras
Control algorithms
Control theory
Efficiency
Ground stations
High definition
Machine learning
Target recognition
Unmanned aerial vehicles
Vehicles
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Summary: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.
ISSN:1530-8669
1530-8677
DOI:10.1155/2022/6902348