LSA64: An Argentinian Sign Language Dataset

Automatic sign language recognition is a research area that encompasses human-computer interaction, computer vision and machine learning. Robust automatic recognition of sign language could assist in the translation process and the integration of hearing-impaired people, as well as the teaching of s...

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Detalles Bibliográficos
Autores principales: Ronchetti, Franco, Quiroga, Facundo, Estrebou, César Armando, Lanzarini, Laura Cristina, Rosete, Alejandro
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2016
Materias:
Ciencias Informáticas
sign language recognition
handshape recognition
lexicon
corpus
automatic recognition
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/56764
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-56764
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
sign language recognition
handshape recognition
lexicon
corpus
automatic recognition
spellingShingle Ciencias Informáticas
sign language recognition
handshape recognition
lexicon
corpus
automatic recognition
Ronchetti, Franco
Quiroga, Facundo
Estrebou, César Armando
Lanzarini, Laura Cristina
Rosete, Alejandro
LSA64: An Argentinian Sign Language Dataset
topic_facet Ciencias Informáticas
sign language recognition
handshape recognition
lexicon
corpus
automatic recognition
description Automatic sign language recognition is a research area that encompasses human-computer interaction, computer vision and machine learning. Robust automatic recognition of sign language could assist in the translation process and the integration of hearing-impaired people, as well as the teaching of sign language to the hearing population. Sign languages differ significantly in different countries and even regions, and their syntax and semantics are different as well from those of written languages. While the techniques for automatic sign language recognition are mostly the same for different languages, training a recognition system for a new language requires having an entire dataset for that language. This paper presents a dataset of 64 signs from the Argentinian Sign Language (LSA). The dataset, called LSA64, contains 3200 videos of 64 different LSA signs recorded by 10 subjects, and is a first step towards building a comprehensive research-level dataset of Argentinian signs, specifically tailored to sign language recognition or other machine learning tasks. The subjects that performed the signs wore colored gloves to ease the hand tracking and segmentation steps, allowing experiments on the dataset to focus specifically on the recognition of signs.
format Objeto de conferencia
Objeto de conferencia
author Ronchetti, Franco
Quiroga, Facundo
Estrebou, César Armando
Lanzarini, Laura Cristina
Rosete, Alejandro
author_facet Ronchetti, Franco
Quiroga, Facundo
Estrebou, César Armando
Lanzarini, Laura Cristina
Rosete, Alejandro
author_sort Ronchetti, Franco
title LSA64: An Argentinian Sign Language Dataset
title_short LSA64: An Argentinian Sign Language Dataset
title_full LSA64: An Argentinian Sign Language Dataset
title_fullStr LSA64: An Argentinian Sign Language Dataset
title_full_unstemmed LSA64: An Argentinian Sign Language Dataset
title_sort lsa64: an argentinian sign language dataset
publishDate 2016
url http://sedici.unlp.edu.ar/handle/10915/56764
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AT quirogafacundo lsa64anargentiniansignlanguagedataset
AT estreboucesararmando lsa64anargentiniansignlanguagedataset
AT lanzarinilauracristina lsa64anargentiniansignlanguagedataset
AT rosetealejandro lsa64anargentiniansignlanguagedataset
bdutipo_str Repositorios
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