Research on UAV Target Recognition and Autonomous 
Tracking System Based on Computer Vision

Tiancheng Zhang

doi:10.70711/aitr.v3i3.8031

Research on UAV Target Recognition and Autonomous Tracking System Based on Computer Vision

Tiancheng Zhang

Abstract

With the rapid advancement of artificial intelligence and computer vision technologies, unmanned aerial vehicles (UAVs) have
been increasingly applied in fields such as intelligent surveillance, disaster rescue, and agricultural inspection. This paper proposes a computer visionbased UAV target recognition and autonomous tracking system to address the limitations of conventional UAV vision systems
in complex environments, such as low accuracy and poor real-time performance. The proposed system employs an enhanced YOLOv8 deep
convolutional neural network for real-time multi-object detection, combined with Kalman filtering and optical flow algorithms for robust
target tracking. Experimental results under varying lighting and occlusion conditions demonstrate that the system achieves superior detection
accuracy, response speed, and stability compared to traditional methods. The findings indicate that the proposed approach effectively enhances
UAVs' autonomous perception and decision-making capabilities, offering strong technical support for visual navigation and intelligent mission
execution.

Keywords

UAV; Computer Vision; Object Detection; Autonomous Tracking; Deep Learning

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References

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DOI: http://dx.doi.org/10.70711/aitr.v3i3.8031

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