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Multimedia content classification metrics for content adaptation

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Detalhes bibliográficos
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 à- 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 frames of the content, and the spatial complexity classification is based on an edge detection algorithm and an image activity measure.
Autores principais:Fernandes, Rui
Outros Autores:Andrade, M.T.
Assunto:Multimedia classification Spatial complexity Temporal complexity Multimedia adaptation
Ano:2015
País:Portugal
Tipo de documento:documento de conferência
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB
Descrição
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 à- 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 frames of the content, and the spatial complexity classification is based on an edge detection algorithm and an image activity measure.