Detail publikace

Detection and Tracking of Moving UAVs

JANOUŠEK, J. MARCOŇ, P. POKORNÝ, J. MIKULKA, J.

Originální název

Detection and Tracking of Moving UAVs

Anglický název

Detection and Tracking of Moving UAVs

Jazyk

en

Originální abstrakt

Detection and recognition of moving objects can provide an effective defense mech-anism for critical infrastructure, airports, government, power stations, and other locations. It is used to increase the security of an internal perimeter with respect to the implementation of defense against the moving UAV (Unmanned Aerial Vehicle). With the rapid growth of the UAV, a very often discussed topic has become defense against unmanned vehicles. Their early detection and destruction can prevent the occurrence of undesirable situations. A camera located on another unmanned vehicle that protects a space will allow detecting and recognizing unwanted targets, and then tracking movements at the best time eliminates further movement of the detected device by release the net. Object detection and recognition are used to find, identify, and categorize moving objects in images and videos. This paper presents comprehensive set of algorithms and tools for detecting and recognizing moving objects. We use the System Toolkit. It is a set of several machine learning, functional and motion techniques for detecting and recognizing objects.

Anglický abstrakt

Detection and recognition of moving objects can provide an effective defense mech-anism for critical infrastructure, airports, government, power stations, and other locations. It is used to increase the security of an internal perimeter with respect to the implementation of defense against the moving UAV (Unmanned Aerial Vehicle). With the rapid growth of the UAV, a very often discussed topic has become defense against unmanned vehicles. Their early detection and destruction can prevent the occurrence of undesirable situations. A camera located on another unmanned vehicle that protects a space will allow detecting and recognizing unwanted targets, and then tracking movements at the best time eliminates further movement of the detected device by release the net. Object detection and recognition are used to find, identify, and categorize moving objects in images and videos. This paper presents comprehensive set of algorithms and tools for detecting and recognizing moving objects. We use the System Toolkit. It is a set of several machine learning, functional and motion techniques for detecting and recognizing objects.

Dokumenty

BibTex


@inproceedings{BUT160874,
  author="Jiří {Janoušek} and Petr {Marcoň} and Josef {Pokorný} and Jan {Mikulka}",
  title="Detection and Tracking of Moving UAVs",
  annote="Detection and recognition of moving objects can provide an effective defense mech-anism for critical infrastructure, airports, government, power stations, and other locations. It is used to increase the security of an internal perimeter with respect to the implementation of defense against the moving UAV (Unmanned Aerial Vehicle). With the rapid growth of the UAV, a very often discussed topic has become defense against unmanned vehicles. Their early detection and destruction can prevent the occurrence of undesirable situations. A camera located on another unmanned vehicle that protects a space will allow detecting and recognizing unwanted targets, and then tracking movements at the best time eliminates further movement of the detected device by release the net.
Object detection and recognition are used to  find, identify, and categorize moving objects in images and videos. This paper presents comprehensive set of algorithms and tools for detecting and recognizing moving objects. We use the System Toolkit. It is a set of several machine learning, functional and motion techniques for detecting and recognizing objects.",
  address="IEEE",
  booktitle="2019 Progress in Electromagnetics Research Symposium (PIERS-Rome)",
  chapter="160874",
  doi="10.1109/PIERS-Spring46901.2019.9017351",
  howpublished="online",
  institution="IEEE",
  year="2019",
  month="june",
  pages="2759--2763",
  publisher="IEEE",
  type="conference paper"
}