Human motion segmentation using active shape models

Detalhes bibliográficos
Autor(a) principal: Maria João M. Vasconcelos
Data de Publicação: 2013
Outros Autores: 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://repositorio-aberto.up.pt/handle/10216/69057
Resumo: Human motion analysis in images is thoroughly related with the developmentof computational techniques capable of automatically identify, track andanalyze relevant structures of the body. In fact, in any system designed for humanmotion analysis from image sequences, the first processing step concerns the identificationof the structures to be analyzed in each of the sequence images, beingthis step commonly referred as image segmentation. Here, a widely used database,the CASIA Gait Database, is used to build Point Distribution Models (PDMs) ofthe human silhouette, including specific joints. The training image dataset used includes14 subjects walking in four different directions, and each shape of the trainingset was represented by a set of labeled landmark points. The contours of thesilhouettes were obtained with the purpose of automatically extract 100 silhouettepoints together with additional 13 anatomic joint points, such as elbows, knees andfeet, to be used as landmarks. In order to obtain the mean shape of the silhouetteas well as its admissible shape variations PDMs for each direction were built. ThePDMs built were finally used in the construction of Active Shape Models (ASMs),which combine the shape model with grey level profiles, with the purpose of furthersegment the modeled silhouettes in new images. The referred technique is aniterative optimization scheme for PDMs allowing initial estimates of pose, scaleand shape of an object to be refined in a new image. The experiments conductedusing this segmentation technique has revealed very encouraging results.
id RCAP_997591e1bd8e9560a0533feb4a039fc9
oai_identifier_str oai:repositorio-aberto.up.pt:10216/69057
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Human motion segmentation using active shape modelsCiências Tecnológicas, Ciências da engenharia e tecnologiasTechnological sciences, Engineering and technologyHuman motion analysis in images is thoroughly related with the developmentof computational techniques capable of automatically identify, track andanalyze relevant structures of the body. In fact, in any system designed for humanmotion analysis from image sequences, the first processing step concerns the identificationof the structures to be analyzed in each of the sequence images, beingthis step commonly referred as image segmentation. Here, a widely used database,the CASIA Gait Database, is used to build Point Distribution Models (PDMs) ofthe human silhouette, including specific joints. The training image dataset used includes14 subjects walking in four different directions, and each shape of the trainingset was represented by a set of labeled landmark points. The contours of thesilhouettes were obtained with the purpose of automatically extract 100 silhouettepoints together with additional 13 anatomic joint points, such as elbows, knees andfeet, to be used as landmarks. In order to obtain the mean shape of the silhouetteas well as its admissible shape variations PDMs for each direction were built. ThePDMs built were finally used in the construction of Active Shape Models (ASMs),which combine the shape model with grey level profiles, with the purpose of furthersegment the modeled silhouettes in new images. The referred technique is aniterative optimization scheme for PDMs allowing initial estimates of pose, scaleand shape of an object to be refined in a new image. The experiments conductedusing this segmentation technique has revealed very encouraging results.20132013-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://repositorio-aberto.up.pt/handle/10216/69057engMaria João M. VasconcelosJoão 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:RCAAP2023-11-29T13:04:55Zoai:repositorio-aberto.up.pt:10216/69057Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:33:16.095089Repositório 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 Human motion segmentation using active shape models
title Human motion segmentation using active shape models
spellingShingle Human motion segmentation using active shape models
Maria João M. Vasconcelos
Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
title_short Human motion segmentation using active shape models
title_full Human motion segmentation using active shape models
title_fullStr Human motion segmentation using active shape models
title_full_unstemmed Human motion segmentation using active shape models
title_sort Human motion segmentation using active shape models
author Maria João M. Vasconcelos
author_facet Maria João M. Vasconcelos
João Manuel R. S. Tavares
author_role author
author2 João Manuel R. S. Tavares
author2_role author
dc.contributor.author.fl_str_mv Maria João M. Vasconcelos
João Manuel R. S. Tavares
dc.subject.por.fl_str_mv Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
topic Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
description Human motion analysis in images is thoroughly related with the developmentof computational techniques capable of automatically identify, track andanalyze relevant structures of the body. In fact, in any system designed for humanmotion analysis from image sequences, the first processing step concerns the identificationof the structures to be analyzed in each of the sequence images, beingthis step commonly referred as image segmentation. Here, a widely used database,the CASIA Gait Database, is used to build Point Distribution Models (PDMs) ofthe human silhouette, including specific joints. The training image dataset used includes14 subjects walking in four different directions, and each shape of the trainingset was represented by a set of labeled landmark points. The contours of thesilhouettes were obtained with the purpose of automatically extract 100 silhouettepoints together with additional 13 anatomic joint points, such as elbows, knees andfeet, to be used as landmarks. In order to obtain the mean shape of the silhouetteas well as its admissible shape variations PDMs for each direction were built. ThePDMs built were finally used in the construction of Active Shape Models (ASMs),which combine the shape model with grey level profiles, with the purpose of furthersegment the modeled silhouettes in new images. The referred technique is aniterative optimization scheme for PDMs allowing initial estimates of pose, scaleand shape of an object to be refined in a new image. The experiments conductedusing this segmentation technique has revealed very encouraging results.
publishDate 2013
dc.date.none.fl_str_mv 2013
2013-01-01T00:00:00Z
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://repositorio-aberto.up.pt/handle/10216/69057
url https://repositorio-aberto.up.pt/handle/10216/69057
dc.language.iso.fl_str_mv eng
language eng
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_ 1799135644040036352