Benchmark RGB-D Gait Datasets: A Systematic Review

Detalhes bibliográficos
Autor(a) principal: João Ferreira Nunes
Data de Publicação: 2019
Outros Autores: Pedro Miguel Moreira, João Manuel R. S. Tavares
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