Thesis Overview: Dynamic Gesture Recognition and its Application to Sign Language
- Autores
- Ronchetti, Franco
- Año de publicación
- 2017
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión enviada
- Descripción
- The automatic recognition of human gestures is a complex multidisciplinary problem that has not yet been completely solved. Since the advent of digital video capture technologies, there have been attempts to recognize dynamic gestures for different purposes. In the recent years, new technologies such as depth sensors or highresolution cameras were incorporated as well as the high processing capacity of the current devices emerged, allowing the new technologies development capable of detecting different movements and acting in real time. Unlike the recognition of the spoken voice, which has been researched for more than forty years, the topic of this thesis is relatively new in the scientific area and it evolves rapidly as new devices appear as well as new computer vision algorithms.
- Materia
-
Ingenierías y Tecnologías
Lenguaje de Signos Argentino (LSA)
automatic recognition - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by/4.0/
- Repositorio
- Institución
- Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
- OAI Identificador
- oai:digital.cic.gba.gob.ar:11746/8580
Ver los metadatos del registro completo
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spelling |
Thesis Overview: Dynamic Gesture Recognition and its Application to Sign LanguageRonchetti, FrancoIngenierías y TecnologíasLenguaje de Signos Argentino (LSA)automatic recognitionThe automatic recognition of human gestures is a complex multidisciplinary problem that has not yet been completely solved. Since the advent of digital video capture technologies, there have been attempts to recognize dynamic gestures for different purposes. In the recent years, new technologies such as depth sensors or highresolution cameras were incorporated as well as the high processing capacity of the current devices emerged, allowing the new technologies development capable of detecting different movements and acting in real time. Unlike the recognition of the spoken voice, which has been researched for more than forty years, the topic of this thesis is relatively new in the scientific area and it evolves rapidly as new devices appear as well as new computer vision algorithms.2017info:eu-repo/semantics/articleinfo:eu-repo/semantics/submittedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/8580enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2025-09-29T13:39:50Zoai:digital.cic.gba.gob.ar:11746/8580Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412025-09-29 13:39:50.564CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse |
dc.title.none.fl_str_mv |
Thesis Overview: Dynamic Gesture Recognition and its Application to Sign Language |
title |
Thesis Overview: Dynamic Gesture Recognition and its Application to Sign Language |
spellingShingle |
Thesis Overview: Dynamic Gesture Recognition and its Application to Sign Language Ronchetti, Franco Ingenierías y Tecnologías Lenguaje de Signos Argentino (LSA) automatic recognition |
title_short |
Thesis Overview: Dynamic Gesture Recognition and its Application to Sign Language |
title_full |
Thesis Overview: Dynamic Gesture Recognition and its Application to Sign Language |
title_fullStr |
Thesis Overview: Dynamic Gesture Recognition and its Application to Sign Language |
title_full_unstemmed |
Thesis Overview: Dynamic Gesture Recognition and its Application to Sign Language |
title_sort |
Thesis Overview: Dynamic Gesture Recognition and its Application to Sign Language |
dc.creator.none.fl_str_mv |
Ronchetti, Franco |
author |
Ronchetti, Franco |
author_facet |
Ronchetti, Franco |
author_role |
author |
dc.subject.none.fl_str_mv |
Ingenierías y Tecnologías Lenguaje de Signos Argentino (LSA) automatic recognition |
topic |
Ingenierías y Tecnologías Lenguaje de Signos Argentino (LSA) automatic recognition |
dc.description.none.fl_txt_mv |
The automatic recognition of human gestures is a complex multidisciplinary problem that has not yet been completely solved. Since the advent of digital video capture technologies, there have been attempts to recognize dynamic gestures for different purposes. In the recent years, new technologies such as depth sensors or highresolution cameras were incorporated as well as the high processing capacity of the current devices emerged, allowing the new technologies development capable of detecting different movements and acting in real time. Unlike the recognition of the spoken voice, which has been researched for more than forty years, the topic of this thesis is relatively new in the scientific area and it evolves rapidly as new devices appear as well as new computer vision algorithms. |
description |
The automatic recognition of human gestures is a complex multidisciplinary problem that has not yet been completely solved. Since the advent of digital video capture technologies, there have been attempts to recognize dynamic gestures for different purposes. In the recent years, new technologies such as depth sensors or highresolution cameras were incorporated as well as the high processing capacity of the current devices emerged, allowing the new technologies development capable of detecting different movements and acting in real time. Unlike the recognition of the spoken voice, which has been researched for more than forty years, the topic of this thesis is relatively new in the scientific area and it evolves rapidly as new devices appear as well as new computer vision algorithms. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/submittedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
submittedVersion |
dc.identifier.none.fl_str_mv |
https://digital.cic.gba.gob.ar/handle/11746/8580 |
url |
https://digital.cic.gba.gob.ar/handle/11746/8580 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by/4.0/ |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:CIC Digital (CICBA) instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Aires instacron:CICBA |
reponame_str |
CIC Digital (CICBA) |
collection |
CIC Digital (CICBA) |
instname_str |
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires |
instacron_str |
CICBA |
institution |
CICBA |
repository.name.fl_str_mv |
CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Aires |
repository.mail.fl_str_mv |
marisa.degiusti@sedici.unlp.edu.ar |
_version_ |
1844618580008632320 |
score |
13.070432 |