TReLSU-HS : A new handshape dataset for Uruguayan Sign Language Recognition.
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.
| 2020 | |
|
LSU Computer vision |
|
| Inglés | |
| Universidad de la República | |
| COLIBRI | |
| https://hdl.handle.net/20.500.12008/25983 | |
| Acceso abierto | |
| Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
| _version_ | 1807522896645455872 |
|---|---|
| author | Stassi Danielli, Ariel Esteban |
| author2 | Delbracio, Maurcio Randall, Gregory |
| author2_role | author author |
| author_facet | Stassi Danielli, Ariel Esteban Delbracio, Maurcio Randall, Gregory |
| author_role | author |
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| collection | COLIBRI |
| dc.contributor.filiacion.none.fl_str_mv | Stassi Danielli Ariel Esteban, Universidad de la República (Uruguay). CENUR Litoral Norte Delbracio Maurcio, Universidad de la República (Uruguay). Facultad de Ingeniería. Randall Gregory, Universidad de la República (Uruguay). Facultad de Ingeniería. |
| dc.coverage.spatial.es.fl_str_mv | Uruguay |
| dc.creator.none.fl_str_mv | Stassi Danielli, Ariel Esteban Delbracio, Maurcio Randall, Gregory |
| dc.date.accessioned.none.fl_str_mv | 2020-11-27T17:26:05Z |
| dc.date.available.none.fl_str_mv | 2020-11-27T17:26:05Z |
| dc.date.issued.none.fl_str_mv | 2020 |
| dc.description.abstract.none.fl_txt_mv | 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. |
| dc.format.mimetype.es.fl_str_mv | application/pdf |
| dc.identifier.citation.es.fl_str_mv | Stassi Danielli, A., Delbracio, M. y Randall, G. TReLSU-HS : A new handshape dataset for Uruguayan Sign Language Recognition [en línea]. Póster, 2020 |
| dc.identifier.uri.none.fl_str_mv | https://hdl.handle.net/20.500.12008/25983 |
| dc.language.iso.none.fl_str_mv | en eng |
| dc.publisher.es.fl_str_mv | IVCSLP |
| dc.relation.ispartof.es.fl_str_mv | 1st International Virtual Conference in Sign Language Processing (IVCSLP), jul 2020 |
| dc.rights.license.none.fl_str_mv | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
| dc.rights.none.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.source.none.fl_str_mv | reponame:COLIBRI instname:Universidad de la República instacron:Universidad de la República |
| dc.subject.es.fl_str_mv | LSU Computer vision |
| dc.title.none.fl_str_mv | TReLSU-HS : A new handshape dataset for Uruguayan Sign Language Recognition. |
| dc.type.es.fl_str_mv | Póster |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/conferenceObject |
| dc.type.version.none.fl_str_mv | info:eu-repo/semantics/publishedVersion |
| description | 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. |
| eu_rights_str_mv | openAccess |
| format | conferenceObject |
| id | COLIBRI_c5a6022de98b04149f8938ad9e152362 |
| identifier_str_mv | Stassi Danielli, A., Delbracio, M. y Randall, G. TReLSU-HS : A new handshape dataset for Uruguayan Sign Language Recognition [en línea]. Póster, 2020 |
| instacron_str | Universidad de la República |
| institution | Universidad de la República |
| instname_str | Universidad de la República |
| language | eng |
| language_invalid_str_mv | en |
| network_acronym_str | COLIBRI |
| network_name_str | COLIBRI |
| oai_identifier_str | oai:colibri.udelar.edu.uy:20.500.12008/25983 |
| publishDate | 2020 |
| reponame_str | COLIBRI |
| repository.mail.fl_str_mv | mabel.seroubian@seciu.edu.uy |
| repository.name.fl_str_mv | COLIBRI - Universidad de la República |
| repository_id_str | 4771 |
| rights_invalid_str_mv | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
| spelling | Stassi Danielli Ariel Esteban, Universidad de la República (Uruguay). CENUR Litoral NorteDelbracio Maurcio, Universidad de la República (Uruguay). Facultad de Ingeniería.Randall Gregory, Universidad de la República (Uruguay). Facultad de Ingeniería.Uruguay2020-11-27T17:26:05Z2020-11-27T17:26:05Z2020Stassi Danielli, A., Delbracio, M. y Randall, G. TReLSU-HS : A new handshape dataset for Uruguayan Sign Language Recognition [en línea]. Póster, 2020https://hdl.handle.net/20.500.12008/25983In 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.Submitted by Ribeiro Jorge (jribeiro@fing.edu.uy) on 2020-11-26T02:15:39Z No. of bitstreams: 2 license_rdf: 23149 bytes, checksum: 1996b8461bc290aef6a27d78c67b6b52 (MD5) SDR20.pdf: 1081160 bytes, checksum: 0a08e56fbeff6d503e81e39f634437df (MD5)Approved for entry into archive by Machado Jimena (jmachado@fing.edu.uy) on 2020-11-27T17:11:00Z (GMT) No. of bitstreams: 2 license_rdf: 23149 bytes, checksum: 1996b8461bc290aef6a27d78c67b6b52 (MD5) SDR20.pdf: 1081160 bytes, checksum: 0a08e56fbeff6d503e81e39f634437df (MD5)Made available in DSpace by Luna Fabiana (fabiana.luna@fic.edu.uy) on 2020-11-27T17:26:05Z (GMT). No. of bitstreams: 2 license_rdf: 23149 bytes, checksum: 1996b8461bc290aef6a27d78c67b6b52 (MD5) SDR20.pdf: 1081160 bytes, checksum: 0a08e56fbeff6d503e81e39f634437df (MD5) Previous issue date: 2020application/pdfenengIVCSLP1st International Virtual Conference in Sign Language Processing (IVCSLP), jul 2020Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad de la República.(Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessLicencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)LSUComputer visionTReLSU-HS : A new handshape dataset for Uruguayan Sign Language Recognition.Pósterinfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionreponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaStassi Danielli, Ariel EstebanDelbracio, MaurcioRandall, GregoryLICENSElicense.txtlicense.txttext/plain; charset=utf-84267http://localhost:8080/xmlui/bitstream/20.500.12008/25983/5/license.txt6429389a7df7277b72b7924fdc7d47a9MD55CC-LICENSElicense_urllicense_urltext/plain; charset=utf-850http://localhost:8080/xmlui/bitstream/20.500.12008/25983/2/license_urla006180e3f5b2ad0b88185d14284c0e0MD52license_textlicense_texttext/html; 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- Universidad de la Repúblicafalse |
| spellingShingle | TReLSU-HS : A new handshape dataset for Uruguayan Sign Language Recognition. Stassi Danielli, Ariel Esteban LSU Computer vision |
| status_str | publishedVersion |
| title | TReLSU-HS : A new handshape dataset for Uruguayan Sign Language Recognition. |
| title_full | TReLSU-HS : A new handshape dataset for Uruguayan Sign Language Recognition. |
| title_fullStr | TReLSU-HS : A new handshape dataset for Uruguayan Sign Language Recognition. |
| title_full_unstemmed | TReLSU-HS : A new handshape dataset for Uruguayan Sign Language Recognition. |
| title_short | TReLSU-HS : A new handshape dataset for Uruguayan Sign Language Recognition. |
| title_sort | TReLSU-HS : A new handshape dataset for Uruguayan Sign Language Recognition. |
| topic | LSU Computer vision |
| url | https://hdl.handle.net/20.500.12008/25983 |
