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Updated: Aug 29, 2025

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Small Target Recognition and Tracking Based on UAV Platform.

Xiangrui Tian1, Yinjun Jia1, Xin Luo1

  • 1College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.

Sensors (Basel, Switzerland)
|September 9, 2022
PubMed
Summary
This summary is machine-generated.

This study enhances aerial small target recognition and tracking using a lightweight YOLOv4 algorithm on multi-rotor UAVs. The improved system achieves higher accuracy and speed, enabling stable tracking of diverse targets like pedestrians and vehicles.

Keywords:
deep learningintelligent recognitionmulti-rotor UAVtarget tracking

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Area of Science:

  • Computer Vision
  • Robotics
  • Artificial Intelligence

Background:

  • Multi-rotor UAVs offer flexible, low-cost aerial surveillance for various applications.
  • Existing small target recognition and tracking algorithms suffer from slow speed, low accuracy, poor robustness, and limited intelligence.

Purpose of the Study:

  • To develop an improved algorithm for robust and intelligent aerial small target recognition and tracking.
  • To enhance the performance of existing algorithms for real-time applications on multi-rotor UAVs.

Main Methods:

  • Lightweight improvement of the YOLOv4 network for small target recognition, tested on the VisDrone dataset.
  • KCF tracking with adaptive learning rate template updates based on response value analysis.
  • Re-search and re-tracking strategy for failed tracking scenarios using recognition results and similarity judgment.
  • Adaptive zoom tracking strategy implemented on a multi-rotor UAV.

Main Results:

  • The improved YOLOv4 algorithm achieved a 1.5% increase in accuracy and a 3.3x increase in speed.
  • The system demonstrated stable tracking of long-distance small targets, including pedestrians, cars, and other UAVs.
  • Adaptive template updates and re-tracking mechanisms improved overall tracking robustness.

Conclusions:

  • The proposed algorithm offers a significant advancement in aerial small target recognition and tracking.
  • The system is suitable for real-time surveillance and monitoring tasks using multi-rotor UAVs.
  • The integration of improved recognition with adaptive tracking provides a robust solution for dynamic environments.