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Título: AN ARCHITECTURE FOR ENHANCING REAL-TIME MULTIMEDIA FLOWS WITH SEMANTIC INFORMATION
Autor: JOSE MATHEUS CARVALHO BOARO
Colaborador(es): SERGIO COLCHER - Orientador
Catalogação: 21/NOV/2023 Língua(s): ENGLISH - UNITED STATES
Tipo: TEXT Subtipo: THESIS
Notas: [pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio.
[en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio.
Referência(s): [pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=64987&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=64987&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.64987
Resumo:
While traditional multimedia systems focused on efficient coding and storage of media types and their temporal relationships, the current demand for rich and customized experiences calls for a deeper understanding of semantic content. In this study, we propose the integration of semantic-level processing into multimedia systems, enriching content with information about real-world entities, such as objects, actions, agents, and language interpretation. The main contribution of this dissertation is the proposal of an architecture for real-time multimedia data enhancement that is able to use machine learning techniques to extract semantic representations and incorporating it into multimedia data streams as a native and basic service. To provide a concrete demonstration of the proposal, we implement two use cases that serve as proofs-of-concept, showing the feasibility of the architecture and showcasing its effectiveness in practical scenarios.
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