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Conference proceeding
On the Detection and Tracking of UAVs in Unreliable Video Feed
Computational Science and Computational Intelligence 11th International Conference, CSCI 2024, Las Vegas, NV, USA, December 11–13, 2024, Proceedings, Part XI, pp.124-131
International Computational Science and Computational Intelligence (CSCI 2024), 11th (Las Vegas, Nevada, USA, 12/11/2024–12/14/2024)
2025
Abstract
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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Details
- Title
- On the Detection and Tracking of UAVs in Unreliable Video Feed
- Publication Details
- Computational Science and Computational Intelligence 11th International Conference, CSCI 2024, Las Vegas, NV, USA, December 11–13, 2024, Proceedings, Part XI, pp.124-131
- Resource Type
- Conference proceeding
- Conference
- International Computational Science and Computational Intelligence (CSCI 2024), 11th (Las Vegas, Nevada, USA, 12/11/2024–12/14/2024)
- Publisher
- Springer Nature Switzerland; Cham
- Copyright
- © 2025 The Author(s), under exclusive license to Springer Nature Switzerland AG
- Identifiers
- 99381469354206600
- Academic Unit
- Dr. Muhammad Harunur Rashid Department of Electrical and Computer Engineering
- Language
- English