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This paper investigates the tracking of Unmanned Aerial Vehicles (UAV) using video feed. Gaussian Mixture Models (GMM) are used to detect the presence of the UAV from a video feed. If the feed is reliable the position of the UAV is detected and tracked. In case the feed is interrupted or becomes unreliable, a Kalman filter is used to predict the location of the UAV. To study the ability of the filter to track the UAV, an actual video capture of flying drone is used, a section of the video is removed to simulate an interruption of the feed. The results show the ability of the filter to accurately predict the location of UAV.

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On the Detection and Tracking of UAVs in Unreliable Video Feed

  • 会议论文

  • 发表日期：

    2025年

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  • Yazan A. Alqudah

摘要

This paper investigates the tracking of Unmanned Aerial Vehicles (UAV) using video feed. Gaussian Mixture Models (GMM) are used to detect the presence of the UAV from a video feed. If the feed is reliable the position of the UAV is detected and tracked. In case the feed is interrupted or becomes unreliable, a Kalman filter is used to predict the location of the UAV. To study the ability of the filter to track the UAV, an actual video capture of flying drone is used, a section of the video is removed to simulate an interruption of the feed. The results show the ability of the filter to accurately predict the location of UAV.