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https://hdl.handle.net/20.500.12008/25983
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| Título: | TReLSU-HS : A new handshape dataset for Uruguayan Sign Language Recognition. |
| Autor: | Stassi Danielli, Ariel Esteban Delbracio, Maurcio Randall, Gregory |
| Tipo: | Póster |
| Palabras clave: | LSU, Computer vision |
| Fecha de publicación: | 2020 |
| Resumen: | 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. |
| Editorial: | IVCSLP |
| EN: | 1st International Virtual Conference in Sign Language Processing (IVCSLP), jul 2020 |
| Citación: | Stassi Danielli, A., Delbracio, M. y Randall, G. TReLSU-HS : A new handshape dataset for Uruguayan Sign Language Recognition [en línea]. Póster, 2020 |
| Cobertura geográfica: | Uruguay |
| Aparece en las colecciones: | Publicaciones académicas y científicas - Instituto de Ingeniería Eléctrica |
Ficheros en este ítem:
| Fichero | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| SDR20.pdf | Póster | 1,06 MB | Adobe PDF | Visualizar/Abrir |
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