Publication result detail

Multiplatform System for Hand Gesture Recognition

BRAVENEC, T.; FRÝZA, T.

Original Title

Multiplatform System for Hand Gesture Recognition

English Title

Multiplatform System for Hand Gesture Recognition

Type

Paper in proceedings (conference paper)

Original 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.

English 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

Key words in English

Hand detection; Gesture recognition; Deep Learning

Authors

BRAVENEC, T.; FRÝZA, T.

RIV year

2021

Released

11.12.2019

Location

Ajman, United Arab Emirates

ISBN

978-1-7281-5341-4

Book

2019 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT 2019)

Pages from

1

Pages to

5

Pages count

5

URL

https://ieeexplore.ieee.org/document/9001762

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"
}