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Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12008/25983 How cite
Title: TReLSU-HS : A new handshape dataset for Uruguayan Sign Language Recognition.
Authors: Stassi Danielli, Ariel Esteban
Delbracio, Maurcio
Randall, Gregory
Type: Póster
Keywords: LSU, Computer vision
Geographic coverage: Uruguay
Issue Date: 2020
Abstract: In this work we present TReLSU-HS, a new database composed of more than 3000 still images for handshape recognition in the context of Uruguayan Sign Language. TReLSU-HS has 30 classes sampled from 5 native signers. The images were obtained from a previous dataset of Uruguayan Sign Language called Léxico TReLSU. Each component image was labeled according to consistent criteria. This database is useful for the computer science community, especially for designing new sign language recognition methods or to better understand the generalization capability of a given recognition system when it is applied to Uruguayan Sign Language data.
Publisher: IVCSLP
IN: 1st International Virtual Conference in Sign Language Processing (IVCSLP), jul 2020
Citation: Stassi Danielli, A., Delbracio, M. y Randall, G. TReLSU-HS : A new handshape dataset for Uruguayan Sign Language Recognition [en línea]. Póster, 2020
License: Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
Appears in Collections:Publicaciones académicas y científicas - Instituto de Ingeniería Eléctrica

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