Deep Learning-based Visual Tracking of UAVs using a PTZ Camera System

Halil Utku Unlu, Phillip Stefan Niehaus, Daniel Chirita, Nikolaos Evangeliou, Anthony Tzes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The visual tracking problem of Unmanned Aerial Vehicles (UAVs) with a Pan-Tilt-Zoom (PTZ) camera system is the subject of this article. Given the background of an image acquired by a PTZ-camera system, a border encompassing a moving object is computed relying on optical flow and the histogram of oriented gradients. Deep Learning (DL) algorithms are trained off-line to decide on the existence of a UAV within this border. Particularly, the ResNet-50 model was trained using a collected data set with more than 50,000 registered positive images. Having identified a UAV, a visual servoing scheme is employed to adjust the PTZ-parameters in order for the border of a detected UAV to span as large as possible the cameras Field of View. The advocated servoing scheme is robust enough against the UAVs rapid maneuvers. Experimental studies are offered to highlight the efficiency of the suggested scheme.

Original languageEnglish (US)
Title of host publicationProceedings
Subtitle of host publicationIECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society
PublisherIEEE Computer Society
Pages638-644
Number of pages7
ISBN (Electronic)9781728148786
DOIs
StatePublished - Oct 2019
Event45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019 - Lisbon, Portugal
Duration: Oct 14 2019Oct 17 2019

Publication series

NameIECON Proceedings (Industrial Electronics Conference)
Volume2019-October

Conference

Conference45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019
CountryPortugal
CityLisbon
Period10/14/1910/17/19

Keywords

  • Deep Learning
  • PTZ camera platform
  • Unmanned Aerial Systems
  • Visual Tracking

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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  • Cite this

    Unlu, H. U., Niehaus, P. S., Chirita, D., Evangeliou, N., & Tzes, A. (2019). Deep Learning-based Visual Tracking of UAVs using a PTZ Camera System. In Proceedings: IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society (pp. 638-644). [8927731] (IECON Proceedings (Industrial Electronics Conference); Vol. 2019-October). IEEE Computer Society. https://doi.org/10.1109/IECON.2019.8927731