Detail publikace
MediaPipe and Its Suitability for Sign Language Recognition
ŠNAJDER, J. KREJSA, J.
Anglický název
MediaPipe and Its Suitability for Sign Language Recognition
Typ
článek ve sborníku mimo WoS a Scopus
Jazyk
en
Originální abstrakt
The paper presents the framework MediaPipe as a tool to extract pose features for the task of word-level isolated sign language recognition. It tests the framework’s suitability on the state-of-the-art sign language dataset AUTSL. Extracted sequences of pose features are classified by the Long Short-Term Memory recurrent neural network constructed with the TensorFlow computational library. The paper describes the proposed method flow, preprocessing of the extracted features, and training. Obtained results are then validated on test datasets, and the impact of face landmarks is evaluated. The top-1 accuracy with face landmarks is 49.89 %, while 53.21 % without them.
Anglický abstrakt
The paper presents the framework MediaPipe as a tool to extract pose features for the task of word-level isolated sign language recognition. It tests the framework’s suitability on the state-of-the-art sign language dataset AUTSL. Extracted sequences of pose features are classified by the Long Short-Term Memory recurrent neural network constructed with the TensorFlow computational library. The paper describes the proposed method flow, preprocessing of the extracted features, and training. Obtained results are then validated on test datasets, and the impact of face landmarks is evaluated. The top-1 accuracy with face landmarks is 49.89 %, while 53.21 % without them.
Klíčová slova anglicky
Sign language recognition; MediaPipe; Long Short-Term Memory; neural network; classification
Vydáno
10.05.2023
Nakladatel
Institute of Thermomechanics of the Czech Academy of Sciences
Místo
Prague
ISBN
ISBN 978-80-87012-84
ISSN
1805-8256
Kniha
ENGINEERING MECHANICS 2023
Číslo edice
1
Strany od–do
251–254
Počet stran
4
BIBTEX
@inproceedings{BUT184379,
author="Jan {Šnajder} and Jiří {Krejsa},
title="MediaPipe and Its Suitability for Sign Language Recognition",
booktitle="ENGINEERING MECHANICS 2023",
year="2023",
month="May",
pages="251--254",
publisher="Institute of Thermomechanics of the Czech Academy of Sciences",
address="Prague",
isbn="ISBN 978-80-87012-84",
issn="1805-8256"
}