Publication detail

Algorithms for Flying Object Detection

JANOUŠEK, J. NOVOTNÝ, J. MARCOŇ, P. ŠIRŮČKOVÁ, A.

Original Title

Algorithms for Flying Object Detection

English Title

Algorithms for Flying Object Detection

Type

conference paper

Language

en

Original Abstract

The object detection and recognition are used for location, identification, and categorization of objects in the images and video. We use video record form flying object in our paper. Video record was transformed into individual images that were preprocessed. In the next step, algorithm for capturing a flying object was applied. Afterwards, algorithm for an object recognition was used. This algorithm is based on Oriented FAST (Features from Accelerated Segment Test) and rotated BRIEF (Binary Robust Independent Elementary Features) methods. The procedures were implemented on a small and affordable computer Raspberry PI 3 model B

English abstract

The object detection and recognition are used for location, identification, and categorization of objects in the images and video. We use video record form flying object in our paper. Video record was transformed into individual images that were preprocessed. In the next step, algorithm for capturing a flying object was applied. Afterwards, algorithm for an object recognition was used. This algorithm is based on Oriented FAST (Features from Accelerated Segment Test) and rotated BRIEF (Binary Robust Independent Elementary Features) methods. The procedures were implemented on a small and affordable computer Raspberry PI 3 model B

Keywords

UAV, Canny filter, drone, object detection, recognition, Viola-Jones detector

Released

01.08.2018

Publisher

IEEE

Location

Toyama, Japan

ISBN

1559-9450

Periodical

Progress In Electromagnetics

State

US

Pages from

782

Pages to

786

Pages count

5

URL

Documents

BibTex


@inproceedings{BUT149041,
  author="Jiří {Janoušek} and Josef {Novotný} and Petr {Marcoň} and Anna {Širůčková}",
  title="Algorithms for Flying Object Detection",
  annote="The object detection and recognition are used for location, identification, and categorization of objects in the images and video. We use video record form flying object in our paper. Video record was transformed into individual images that were preprocessed. In the next step, algorithm for capturing a flying object was applied. Afterwards, algorithm for an object recognition was used. This algorithm is based on Oriented FAST (Features from Accelerated Segment Test) and rotated BRIEF (Binary Robust Independent Elementary Features) methods. The procedures were implemented on a small and affordable computer Raspberry PI 3 model B",
  address="IEEE",
  booktitle="Progress in Electromagnetics Research Symposium (PIERS-Toyama)",
  chapter="149041",
  doi="10.23919/PIERS.2018.8598196",
  howpublished="online",
  institution="IEEE",
  year="2018",
  month="august",
  pages="782--786",
  publisher="IEEE",
  type="conference paper"
}