Publication detail

Embedded Video Processing on Raspberry Pi

ÁRVA, G. FRÝZA, T.

Original Title

Embedded Video Processing on Raspberry Pi

English Title

Embedded Video Processing on Raspberry Pi

Type

conference paper

Language

en

Original Abstract

The paper presents a study of existing methods for motion and face detection algorithms and their application to the on-board miniature Raspberry Pi computer. The algorithms realized by OpenCV functions were modified to optimize their operation on the mentioned platform, which could be used as an embedded surveillance system. The paper also mentions the training of a custom classifier for hand detection, what could be further used as a basis for detecting hand gestures.

English abstract

The paper presents a study of existing methods for motion and face detection algorithms and their application to the on-board miniature Raspberry Pi computer. The algorithms realized by OpenCV functions were modified to optimize their operation on the mentioned platform, which could be used as an embedded surveillance system. The paper also mentions the training of a custom classifier for hand detection, what could be further used as a basis for detecting hand gestures.

Keywords

OpenCV, Raspberry Pi, motion detection, cascade classifiers, video surveillance

Released

20.04.2017

Location

Brno, Czech Republic

ISBN

978-1-5090-4591-4

Book

Proceedings of 27th International Conference Radioelektronika 2017

Pages from

1

Pages to

4

Pages count

4

URL

BibTex


@inproceedings{BUT137522,
  author="Gábor {Árva} and Tomáš {Frýza}",
  title="Embedded Video Processing on Raspberry Pi",
  annote="The paper presents a study of existing methods for motion and face detection algorithms and their application to the on-board miniature Raspberry Pi computer. The algorithms realized by OpenCV functions were modified to optimize their operation on the mentioned platform, which could be used as an embedded surveillance system. The paper also mentions the training of a custom classifier for hand detection, what could be further used as a basis for detecting hand gestures.",
  booktitle="Proceedings of 27th International Conference Radioelektronika 2017",
  chapter="137522",
  doi="10.1109/RADIOELEK.2017.7937598",
  howpublished="online",
  year="2017",
  month="april",
  pages="1--4",
  type="conference paper"
}