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| Research on Unmanned Aerial Vehicle to Ground Vehicle Target Detection Algorithm Based on Multiscale Fusion Method |
| ZHANG Li-guo,JIANG Yi-xuan,TIAN Guang-jun |
| School of Electrical Engineering,Yanshan University,Qinhuangdao, Hebei 066004, China |
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Abstract With the development of drone technology,the use of drone images for ground vehicle target recognition is of great significance both in rescue and disaster relief and in traffic management. However,in actual use,due to the flight height and other reasons,the target in the image is generally small in size and the feature information is not obvious. It is difficult to detect the target using existing algorithms. Therefore,an image multi-target detection method based on multi-scale fusion is proposed. Using Faster R-CNN as the basic framework,the feature information of different levels is fused,and the context information is combined to realize the detection of small targets in unmanned aerial vehicle images. The VisDrone dataset is used to perform ground inspection on ground vehicles. Experiments have shown that the detection of ground vehicle targets by drones has achieved good results. The accuracy of the algorithm used has reached 88%, which is an increase of 3.8% compared with other algorithms the above.
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Received: 03 January 2020
Published: 01 December 2021
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2021, Vol. 42 
