Result Details

Multiplatform System for Hand Gesture Recognition

BRAVENEC, T.; FRÝZA, T. Multiplatform System for Hand Gesture Recognition. In 2019 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT 2019). Ajman, United Arab Emirates: 2019. p. 1-5. ISBN: 978-1-7281-5341-4.
Type
conference paper
Language
English
Authors
Bravenec Tomáš, Ing., Ph.D., UREL (FEEC)
Frýza Tomáš, doc. Ing., Ph.D., UREL (FEEC)
Abstract

This paper is focused on hand gestures and finger detection in still images and video sequences. The paper also contains a brief testing of different approaches to hand gesture detections as well as the realization of the platform independent application written in Python using OpenCV and PyTorch libraries, that can show a selected image or play a video sequence with highlighted recognized gestures.

Keywords

Hand detection; Gesture recognition; Deep Learning

URL
Published
2019
Pages
1–5
Proceedings
2019 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT 2019)
Conference
IEEE International Symposium on Signal Processing and Information Technology (ISSPIT 2019)
ISBN
978-1-7281-5341-4
Place
Ajman, United Arab Emirates
DOI
10.1109/ISSPIT47144.2019.9001762
UT WoS
000568621300039
EID Scopus
2-s2.0-85081377991
BibTeX 
@inproceedings{BUT159799,
  author="Tomáš {Bravenec} and Tomáš {Frýza}",
  title="Multiplatform System for Hand Gesture Recognition",
  booktitle="2019 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT 2019)",
  year="2019",
  pages="1--5",
  address="Ajman, United Arab Emirates",
  doi="10.1109/ISSPIT47144.2019.9001762",
  isbn="978-1-7281-5341-4",
  url="https://ieeexplore.ieee.org/document/9001762"
}
Departments
Department of Radio Electronics (UREL)
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