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On-board UAV Pilots Identification in Counter UAV Images

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Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1474))

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Abstract

Among Unmanned Aerial Vehicles (UAV) countermeasures, the detection of the drone position and the identification of the human pilot represent two crucial tasks, as demonstrated by the attention already obtained from security agencies in different countries. Many research works focus on the UAV detection but they rarely take into account the problem of the detection of the pilot of another approaching UAV. This work proposes a full autonomous pipeline that, taking images from a flying UAV, can detect the humans in the scene and recognizing the eventual presence of the pilot(s). The system has been designed to be run on-board of the UAV, and tests have been performed on an NVIDIA Jetson TX2. Moreover, the SnT-ARG-PilotDetect dataset, designed to assess the capabilities to identify the UAV pilots in realistic scenarios, is introduced for the first time and made publicly available. An accurate comparison of different classification approaches on the pilot and non-pilot images of the proposed dataset has been performed, and results show the validity of the proposed pipeline for piloting behavior classification.

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Notes

  1. 1.

    The dataset is available at https://github.com/dcazzato/SnT-Arg-PilotDetect.

  2. 2.

    Available at https://github.com/google/automl/tree/master/efficientdet.

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Acknowledgments

We thank Prof. Dr. Miguel Angel Olivares-Mendez for his technical support in the creation of the dataset.

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Authors and Affiliations

  1. Interdisciplinary Center for Security, Reliability and Trust (SnT), University of Luxembourg, 29, Avenue J. F. Kennedy, 1855, Luxembourg, Luxembourg

    Dario Cazzato, Claudio Cimarelli & Holger Voos

Authors
  1. Dario Cazzato
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  2. Claudio Cimarelli
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  3. Holger Voos
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Corresponding author

Correspondence to Dario Cazzato .

Editor information

Editors and Affiliations

  1. IRISA, University of Rennes 1, Rennes, France

    Kadi Bouatouch

  2. Universidade do Porto, Porto, Portugal

    A. Augusto de Sousa

  3. University of Genova, Genova, Italy

    Manuela Chessa

  4. Mines ParisTech, Paris, France

    Alexis Paljic

  5. Linnaeus University, Växjö, Sweden

    Andreas Kerren

  6. French Civil Aviation University (ENAC), Toulouse, France

    Christophe Hurter

  7. Università di Catania, Catania, Italy

    Giovanni Maria Farinella

  8. Universitat de Barcelona, Barcelona, Spain

    Petia Radeva

  9. Escola Superior de Tecnologia de Setúbal, Setúbal, Portugal

    Jose Braz

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Cazzato, D., Cimarelli, C., Voos, H. (2022). On-board UAV Pilots Identification in Counter UAV Images. In: Bouatouch, K., et al. Computer Vision, Imaging and Computer Graphics Theory and Applications. VISIGRAPP 2020. Communications in Computer and Information Science, vol 1474. Springer, Cham. https://doi.org/10.1007/978-3-030-94893-1_19

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  • DOI: https://doi.org/10.1007/978-3-030-94893-1_19

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  • Print ISBN: 978-3-030-94892-4

  • Online ISBN: 978-3-030-94893-1

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