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Unauthorized drone flying can prompt disruptions in critical facilities such as airports or railways. To prevent these situations, we propose a surveillance system that can sense malicious and/or illicit aerial targets. The idea is to track moving aerial objects using a static camera and when a tracked object is considered suspicious, the camera zooms in to take a snapshot of the target. This snapshot is then classified as an aircraft, drone, bird or cloud. In this work, we propose the classical technique of two-frame background subtraction to detect moving objects. We use the discrete Kalman filter to predict the location of each object and the Jonker-Volgenant algorithm to match objects between consecutive image frames. A deep residual network, trained with transfer learning, is used for image classification. The residual net ResNet-50 developed for the ILSVRC competition was retrained for this purpose. The performance of the system was evaluated with positive results in real-world conditions. The system was able to track multiple aerial objects with acceptable accuracy and the classification system also exhibited high performance.
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\nZenodo’s general policies and Terms of Use apply to all content.
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", "description": "Open repository for EU-funded research outputs from Horizon Europe, Euratom and earlier Framework Programmes.", "organizations": [ { "id": "00k4n6c32" } ], "page": "The EU Open Research Repository is a Zenodo-community dedicated to fostering open science and enhancing the visibility and accessibility of research outputs funded by the European Union. The community is managed by CERN on behalf of the European Commission.
\nThe mission of the repository is to support the implementation of the EU's open science policy, providing a trusted and comprehensive space for researchers to share their research outputs such as data, software, reports, presentations, posters and more. The EU Open Research Repository simplifies the process of complying with open science requirements, ensuring that research outputs from Horizon Europe, Euratom, and earlier Framework Programmes are freely accessible, thereby accelerating scientific discovery and innovation.
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\r\n", "page": "Protecting European borders against drug trafficking is crucial, which is currently aggravated by the increasing use of small aircraft that allows for almost undetected border crossings, especially coastal borders. Therefore, a system is needed that can add to existing surveillance means and significantly increases the detection probability, particularly for small aircraft. Moreover a prediction of the landing or dropping zone of the aircraft is required.
\r\n\r\nThe ALFA surveillance system, to be developed within the framework of this project, is offering these capabilities. It will bridge the existing capability gap of current operational surveillance systems for border control.
\r\n\r\nThe main objective of the project is the development of a system for timely detection, classification and understanding of the intentions of suspected air targets. The system will also provide a prediction of the landing site or dropping zone. ALFA will contribute to the following EU strategic goals:
\r\n\r\n