Small Target Recognition and Tracking Based on UAV Platform

Target recognition and tracking based on multi-rotor UAVs have the advantages of low cost and high flexibility. It can monitor low-altitude targets with high intensity. It has great application prospects in national defense, military, and civil fields. The existing algorithms for aerial small target...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Vol. 22; no. 17; p. 6579
Main Authors: Tian, Xiangrui, Jia, Yinjun, Luo, Xin, Yin, Jie
Format: Journal Article
Language:English
Published: Basel MDPI AG 31.08.2022
MDPI
Subjects:
Accuracy
Adaptive learning
Algorithms
deep learning
Drone aircraft
intelligent recognition
Machine vision
Methods
multi-rotor UAV
Neural networks
Remote sensing
Target recognition
target tracking
Technology application
China
ISSN:1424-8220, 1424-8220
Online Access:Get full text
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Summary:Target recognition and tracking based on multi-rotor UAVs have the advantages of low cost and high flexibility. It can monitor low-altitude targets with high intensity. It has great application prospects in national defense, military, and civil fields. The existing algorithms for aerial small target recognition and tracking have the disadvantages of slow speed, low accuracy, poor robustness, and insufficient intelligence. Aiming at the problems of existing algorithms, this paper first makes a lightweight improvement for the YOLOv4 network recognition algorithm suitable for small target recognition and tests it on the VisDrone dataset. The accuracy of the improved algorithm is increased by 1.5% and the speed is increased by 3.3 times. Then, by analyzing the response value, the KCF tracking situation is judged, and the template update of the adaptive learning rate is realized. When the tracking fails, the target is re-searched and tracked based on the recognition results and the similarity judgment. Finally, experiments are carried out on the multi-rotor UAV, and the adaptive zoom tracking strategy is designed to track pedestrians, cars, and UAVs. The results show that the proposed algorithm can achieve stable tracking of long-distance small targets.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s22176579