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Authors: Ariel E. Stassi 1 ; Marcela Tancredi 2 ; Roberto Aguirre 3 ; Alvaro Gómez 4 ; Bruno Carballido 3 ; 5 ; Andrés Méndez 5 ; Sergio Beheregaray 6 ; Alejandro Fojo 2 ; Víctor Koleszar 5 and Gregory Randall 4

Affiliations: 1 Centro Universitario Regional Litoral Norte, Universidad de la República, Paysandú, Uruguay ; 2 Facultad de Humanidades y Ciencias de la Educación, Universidad de la República, Uruguay ; 3 Centro de Investigación Básica en Psicología, Facultad de Psicología, Universidad de la República, Uruguay ; 4 Instituto de Ingeniería Eléctrica, Facultad de Ingeniería, Universidad de la República, Uruguay ; 5 Centro Interdisciplinario en Cognición para la Enseñanza y el Aprendizaje, Universidad de la República, Uruguay ; 6 Centro de Investigación y Desarrollo para la Persona Sorda, Uruguay

Keyword(s): Uruguayan Sign Language, Sign Language Recognition, Public Dataset.

Abstract: The first Uruguayan Sign Language public dataset for automatic recognition (LSU-DS) is presented. The dataset can be used both for linguistic studies and for automatic recognition at different levels: alphabet, isolated signs, and sentences. LSU-DS consists of several repetitions of three linguistic tasks by 10 signers. The registers were acquired in an indoor context and with controlled lighting. The signers were freely dressed without gloves or specific markers for recognition. The recordings were acquired by 3 simultaneous cameras calibrated for stereo vision. The dataset is openly available to the community and includes gloss information as well as both the videos and the 3D models generated by OpenPose and MediaPipe for all acquired sequences.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Stassi, A.; Tancredi, M.; Aguirre, R.; Gómez, A.; Carballido, B.; Méndez, A.; Beheregaray, S.; Fojo, A.; Koleszar, V. and Randall, G. (2022). LSU-DS: An Uruguayan Sign Language Public Dataset for Automatic Recognition. In Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-549-4; ISSN 2184-4313, SciTePress, pages 697-705. DOI: 10.5220/0010894200003122

@conference{icpram22,
author={Ariel E. Stassi. and Marcela Tancredi. and Roberto Aguirre. and Alvaro Gómez. and Bruno Carballido. and Andrés Méndez. and Sergio Beheregaray. and Alejandro Fojo. and Víctor Koleszar. and Gregory Randall.},
title={LSU-DS: An Uruguayan Sign Language Public Dataset for Automatic Recognition},
booktitle={Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2022},
pages={697-705},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010894200003122},
isbn={978-989-758-549-4},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - LSU-DS: An Uruguayan Sign Language Public Dataset for Automatic Recognition
SN - 978-989-758-549-4
IS - 2184-4313
AU - Stassi, A.
AU - Tancredi, M.
AU - Aguirre, R.
AU - Gómez, A.
AU - Carballido, B.
AU - Méndez, A.
AU - Beheregaray, S.
AU - Fojo, A.
AU - Koleszar, V.
AU - Randall, G.
PY - 2022
SP - 697
EP - 705
DO - 10.5220/0010894200003122
PB - SciTePress

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