Publication detail

Czech Sign Language Single Hand Alphabet Classification with MediaPipe

ŠNAJDER, J. BEDNAŘÍK, J.

Original Title

Czech Sign Language Single Hand Alphabet Classification with MediaPipe

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

The paper presents the classification of static images of the single-handed Czech sign language alphabet. It uses the framework MediaPipe for annotation, and the classification is performed by a neural network using the TensorFlow computational library. The flow of the proposed method, data acquisition, preprocessing, and training are described in the paper. Obtained results consist of the classification success rate of the validation dataset for various MediaPipe configurations. The overall success rate was around 94%.

Keywords

Czech sign language, Fingerspelling, Classification, Mediapipe, Neural network

Authors

ŠNAJDER, J.; BEDNAŘÍK, J.

Released

9. 5. 2022

Publisher

Institute of Theoretical and Applied Mechanics of the Czech Academy of Sciences

Location

Prague

ISBN

ISBN 978-80-86246-51

Book

ENGINEERING MECHANICS 2022

Edition number

1

ISBN

1805-8256

Periodical

Engineering Mechanics ....

State

Czech Republic

Pages from

381

Pages to

384

Pages count

4

URL

https://www.engmech.cz/improc/2022/381.pdf

BibTex

@inproceedings{BUT178377,
  author="Jan {Šnajder} and Josef {Bednařík}",
  title="Czech Sign Language Single Hand Alphabet Classification with MediaPipe",
  booktitle="ENGINEERING MECHANICS 2022",
  year="2022",
  journal="Engineering Mechanics ....",
  number="1",
  pages="381--384",
  publisher="Institute of Theoretical and Applied Mechanics of the Czech Academy of Sciences",
  address="Prague",
  doi="10.21495/51­2­381",
  isbn="ISBN 978-80-86246-51",
  issn="1805-8256",
  url="https://www.engmech.cz/improc/2022/381.pdf"
}