Multimedia content classification metrics for content adaptation

Detalhes bibliográficos
Autor(a) principal: Fernandes, Rui
Data de Publicação: 2016
Outros Autores: Andrade, M.T.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10198/16447
Resumo: Multimedia content consumption is very popular nowadays. However, not every content can be consumed in its original format: the combination of content, transport and access networks, consumption device and usage environment characteristics may all pose restrictions to that purpose. One way to provide the best possible quality to the user is to adapt the content according to these restrictions as well as user preferences. This adaptation stage can be best executed if knowledge about the content is known a-priori. In order to provide this knowledge we classify the content based on metrics to define its temporal and spatial complexity. The temporal complexity classification is based on the Motion Vectors of the predictive encoded frames and on the difference between frames. The spatial complexity classification is based on different implementations of an edge detection algorithm and an image activity measure.
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spelling Multimedia content classification metrics for content adaptationMultimedia classificationTemporal complexitySpatial complexityMultimedia adaptationMultimedia content consumption is very popular nowadays. However, not every content can be consumed in its original format: the combination of content, transport and access networks, consumption device and usage environment characteristics may all pose restrictions to that purpose. One way to provide the best possible quality to the user is to adapt the content according to these restrictions as well as user preferences. This adaptation stage can be best executed if knowledge about the content is known a-priori. In order to provide this knowledge we classify the content based on metrics to define its temporal and spatial complexity. The temporal complexity classification is based on the Motion Vectors of the predictive encoded frames and on the difference between frames. The spatial complexity classification is based on different implementations of an edge detection algorithm and an image activity measure.Biblioteca Digital do IPBFernandes, RuiAndrade, M.T.2018-03-21T10:23:28Z20162016-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10198/16447engFernandes, Rui; Andrade, M.T. (2016). Multimedia content classification metrics for content adaptation. U.Porto Journal of Engineering. ISSN 2183-6493. 2:2, p. 14-252183-6493info: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:RCAAP2023-11-21T10:38:01Zoai:bibliotecadigital.ipb.pt:10198/16447Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:05:51.771313Repositório 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 Multimedia content classification metrics for content adaptation
title Multimedia content classification metrics for content adaptation
spellingShingle Multimedia content classification metrics for content adaptation
Fernandes, Rui
Multimedia classification
Temporal complexity
Spatial complexity
Multimedia adaptation
title_short Multimedia content classification metrics for content adaptation
title_full Multimedia content classification metrics for content adaptation
title_fullStr Multimedia content classification metrics for content adaptation
title_full_unstemmed Multimedia content classification metrics for content adaptation
title_sort Multimedia content classification metrics for content adaptation
author Fernandes, Rui
author_facet Fernandes, Rui
Andrade, M.T.
author_role author
author2 Andrade, M.T.
author2_role author
dc.contributor.none.fl_str_mv Biblioteca Digital do IPB
dc.contributor.author.fl_str_mv Fernandes, Rui
Andrade, M.T.
dc.subject.por.fl_str_mv Multimedia classification
Temporal complexity
Spatial complexity
Multimedia adaptation
topic Multimedia classification
Temporal complexity
Spatial complexity
Multimedia adaptation
description Multimedia content consumption is very popular nowadays. However, not every content can be consumed in its original format: the combination of content, transport and access networks, consumption device and usage environment characteristics may all pose restrictions to that purpose. One way to provide the best possible quality to the user is to adapt the content according to these restrictions as well as user preferences. This adaptation stage can be best executed if knowledge about the content is known a-priori. In order to provide this knowledge we classify the content based on metrics to define its temporal and spatial complexity. The temporal complexity classification is based on the Motion Vectors of the predictive encoded frames and on the difference between frames. The spatial complexity classification is based on different implementations of an edge detection algorithm and an image activity measure.
publishDate 2016
dc.date.none.fl_str_mv 2016
2016-01-01T00:00:00Z
2018-03-21T10:23:28Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10198/16447
url http://hdl.handle.net/10198/16447
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Fernandes, Rui; Andrade, M.T. (2016). Multimedia content classification metrics for content adaptation. U.Porto Journal of Engineering. ISSN 2183-6493. 2:2, p. 14-25
2183-6493
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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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
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