Benchmark RGB-D Gait Datasets: A Systematic Review
Autor(a) principal: | |
---|---|
Data de Publicação: | 2019 |
Outros Autores: | , |
Tipo de documento: | Livro |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/10216/124743 |
Resumo: | Human motion analysis has proven to be a great source of information for a wide range of applications. Several approaches for a detailed and accurate motion analysis have been proposed in the literature, as well as an almost proportional number of dedicated datasets. The relatively recent arrival of depth sensors contributed to an increasing interest in this research area and also to the emergence of a new type of motion datasets. This work focuses on a systematic review of publicly available depth-based datasets, encompassing human gait data which is used for person recognition and/or classification purposes. We have conducted this systematic review using the Scopus database. The herein presented survey, which to the best of our knowledge is the first one dedicated to this type of datasets, is intended to inform and aid researchers on the selection of the most suitable datasets to develop, test and compare their algorithms. (c) Springer Nature Switzerland AG 2019. |
id |
RCAP_65e1ac144e3290a1f88152ab30cba13e |
---|---|
oai_identifier_str |
oai:repositorio-aberto.up.pt:10216/124743 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Benchmark RGB-D Gait Datasets: A Systematic ReviewCiências Tecnológicas, Ciências médicas e da saúdeTechnological sciences, Medical and Health sciencesHuman motion analysis has proven to be a great source of information for a wide range of applications. Several approaches for a detailed and accurate motion analysis have been proposed in the literature, as well as an almost proportional number of dedicated datasets. The relatively recent arrival of depth sensors contributed to an increasing interest in this research area and also to the emergence of a new type of motion datasets. This work focuses on a systematic review of publicly available depth-based datasets, encompassing human gait data which is used for person recognition and/or classification purposes. We have conducted this systematic review using the Scopus database. The herein presented survey, which to the best of our knowledge is the first one dedicated to this type of datasets, is intended to inform and aid researchers on the selection of the most suitable datasets to develop, test and compare their algorithms. (c) Springer Nature Switzerland AG 2019.2019-102019-10-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://hdl.handle.net/10216/124743eng10.1007/978-3-030-32040-9_38João Ferreira NunesPedro Miguel MoreiraJoão Manuel R. S. Tavaresinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T13:19:41Zoai:repositorio-aberto.up.pt:10216/124743Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:38:33.554517Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Benchmark RGB-D Gait Datasets: A Systematic Review |
title |
Benchmark RGB-D Gait Datasets: A Systematic Review |
spellingShingle |
Benchmark RGB-D Gait Datasets: A Systematic Review João Ferreira Nunes Ciências Tecnológicas, Ciências médicas e da saúde Technological sciences, Medical and Health sciences |
title_short |
Benchmark RGB-D Gait Datasets: A Systematic Review |
title_full |
Benchmark RGB-D Gait Datasets: A Systematic Review |
title_fullStr |
Benchmark RGB-D Gait Datasets: A Systematic Review |
title_full_unstemmed |
Benchmark RGB-D Gait Datasets: A Systematic Review |
title_sort |
Benchmark RGB-D Gait Datasets: A Systematic Review |
author |
João Ferreira Nunes |
author_facet |
João Ferreira Nunes Pedro Miguel Moreira João Manuel R. S. Tavares |
author_role |
author |
author2 |
Pedro Miguel Moreira João Manuel R. S. Tavares |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
João Ferreira Nunes Pedro Miguel Moreira João Manuel R. S. Tavares |
dc.subject.por.fl_str_mv |
Ciências Tecnológicas, Ciências médicas e da saúde Technological sciences, Medical and Health sciences |
topic |
Ciências Tecnológicas, Ciências médicas e da saúde Technological sciences, Medical and Health sciences |
description |
Human motion analysis has proven to be a great source of information for a wide range of applications. Several approaches for a detailed and accurate motion analysis have been proposed in the literature, as well as an almost proportional number of dedicated datasets. The relatively recent arrival of depth sensors contributed to an increasing interest in this research area and also to the emergence of a new type of motion datasets. This work focuses on a systematic review of publicly available depth-based datasets, encompassing human gait data which is used for person recognition and/or classification purposes. We have conducted this systematic review using the Scopus database. The herein presented survey, which to the best of our knowledge is the first one dedicated to this type of datasets, is intended to inform and aid researchers on the selection of the most suitable datasets to develop, test and compare their algorithms. (c) Springer Nature Switzerland AG 2019. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-10 2019-10-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/book |
format |
book |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10216/124743 |
url |
https://hdl.handle.net/10216/124743 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1007/978-3-030-32040-9_38 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799135699830571008 |