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Improved UAV-to-Ground Multi-Target Tracking Algorithm Based on StrongSORT.

Xinyu Cao1, Zhuo Wang1, Bowen Zheng1

  • 1School of Computer and Control Engineering, Northeast Forestry University, Harbin 150006, China.

Sensors (Basel, Switzerland)
|November 25, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces an optimized framework for real-time multi-target tracking using Unmanned Aerial Vehicles (UAVs). The system significantly improves tracking accuracy and speed for ground robots in complex environments.

Keywords:
OSNetStrongSORTsmall target detectionunmanned aerial vehicle

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Area of Science:

  • Robotics
  • Computer Vision
  • Artificial Intelligence

Background:

  • Unmanned Aerial Vehicles (UAVs) are critical for aerial monitoring and reconnaissance.
  • Vision-based multi-target tracking presents significant challenges for UAVs, especially in dynamic environments.
  • Existing multi-target tracking algorithms struggle with issues like target occlusion, camera jitter, and small target sizes.

Purpose of the Study:

  • To develop a robust framework for real-time multi-target tracking of ground robots using UAVs.
  • To enhance the performance of detection and re-identification networks for improved real-time target detection.
  • To address limitations in current tracking algorithms, ensuring reliable tracking in challenging conditions.

Main Methods:

  • Utilized the YOLOv5n detection algorithm for training on a custom dataset.
  • Implemented the StrongSORT tracking algorithm, integrating optimized YOLOv5n model weights.
  • Focused on optimizing detection and re-identification networks for enhanced real-time performance.

Main Results:

  • Achieved a sixfold decrease in ID switches (IDSW).
  • Increased IDF1 score by 7.93% and reduced false positives (FP) by 30.28%.
  • Reached a tracking speed of 38 frames per second, meeting real-time requirements.

Conclusions:

  • The developed framework effectively fulfills real-time tracking requirements for UAV platforms.
  • The optimized YOLOv5n and StrongSORT integration provides dependable solutions for dynamic multi-target tracking.
  • This advancement supports enhanced aerial reconnaissance and monitoring capabilities in complex terrains.