GRIDDS - a gait recognition image and depth dataset

Bibliographic Details
Main Author: Nunes, João
Publication Date: 2019
Other Authors: Moreira, Pedro Miguel, Tavares, João Manuel R. S.
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/20.500.11960/3099
Summary: Several approaches based on human gait have been proposed in the literature, either for medical research reasons, smart surveillance, human-machine interaction, or other purposes, whose validation highly depends on the access to common input data through available datasets, enabling a coherent performance comparison. The advent of depth sensors leveraged the emergence of novel approaches and, consequently, the usage of new datasets. In this work we present the GRIDDS - A Gait Recognition Image and Depth Dataset, a new and publicly available gait depth-based dataset that can be used mostly for person and gender recognition purposes.
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spelling GRIDDS - a gait recognition image and depth datasetGait DatasetPerson RecognitionGender RecognitionRGB-D SensorsGRIDDSSeveral approaches based on human gait have been proposed in the literature, either for medical research reasons, smart surveillance, human-machine interaction, or other purposes, whose validation highly depends on the access to common input data through available datasets, enabling a coherent performance comparison. The advent of depth sensors leveraged the emergence of novel approaches and, consequently, the usage of new datasets. In this work we present the GRIDDS - A Gait Recognition Image and Depth Dataset, a new and publicly available gait depth-based dataset that can be used mostly for person and gender recognition purposes.2023-01-06T18:40:24Z2019-01-01T00:00:00Z20192022-11-02T16:56:26Zbook partinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/20.500.11960/3099eng978-3-030-32039-3978-3-030-32040-92212-94132212-939110.1007/978-3-030-32040-9_36metadata only accessinfo:eu-repo/semantics/openAccessNunes, JoãoMoreira, Pedro MiguelTavares, João Manuel R. S.reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-04-11T08:09:37Zoai:repositorio.ipvc.pt:20.500.11960/3099Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T13:27:45.744705Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv GRIDDS - a gait recognition image and depth dataset
title GRIDDS - a gait recognition image and depth dataset
spellingShingle GRIDDS - a gait recognition image and depth dataset
Nunes, João
Gait Dataset
Person Recognition
Gender Recognition
RGB-D Sensors
GRIDDS
title_short GRIDDS - a gait recognition image and depth dataset
title_full GRIDDS - a gait recognition image and depth dataset
title_fullStr GRIDDS - a gait recognition image and depth dataset
title_full_unstemmed GRIDDS - a gait recognition image and depth dataset
title_sort GRIDDS - a gait recognition image and depth dataset
author Nunes, João
author_facet Nunes, João
Moreira, Pedro Miguel
Tavares, João Manuel R. S.
author_role author
author2 Moreira, Pedro Miguel
Tavares, João Manuel R. S.
author2_role author
author
dc.contributor.author.fl_str_mv Nunes, João
Moreira, Pedro Miguel
Tavares, João Manuel R. S.
dc.subject.por.fl_str_mv Gait Dataset
Person Recognition
Gender Recognition
RGB-D Sensors
GRIDDS
topic Gait Dataset
Person Recognition
Gender Recognition
RGB-D Sensors
GRIDDS
description Several approaches based on human gait have been proposed in the literature, either for medical research reasons, smart surveillance, human-machine interaction, or other purposes, whose validation highly depends on the access to common input data through available datasets, enabling a coherent performance comparison. The advent of depth sensors leveraged the emergence of novel approaches and, consequently, the usage of new datasets. In this work we present the GRIDDS - A Gait Recognition Image and Depth Dataset, a new and publicly available gait depth-based dataset that can be used mostly for person and gender recognition purposes.
publishDate 2019
dc.date.none.fl_str_mv 2019-01-01T00:00:00Z
2019
2022-11-02T16:56:26Z
2023-01-06T18:40:24Z
dc.type.driver.fl_str_mv book part
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/20.500.11960/3099
url http://hdl.handle.net/20.500.11960/3099
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 978-3-030-32039-3
978-3-030-32040-9
2212-9413
2212-9391
10.1007/978-3-030-32040-9_36
dc.rights.driver.fl_str_mv metadata only access
info:eu-repo/semantics/openAccess
rights_invalid_str_mv metadata only access
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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