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Estatística
Título: A ROBUST WORKFLOW FOR PERSON TRACKING AND META-DATA GENERATION IN VIDEOS
Autor: RAFAEL ANTONIO PINTO PENA
Colaborador(es): HELIO CORTES VIEIRA LOPES - Orientador
Catalogação: 23/JUN/2021 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=53394&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=53394&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.53394
Resumo:
The amount of recorded video in the world is increasing a lot due not only to the humans interests and habits regarding this kind of media, but also the diversity of devices used to create them. However, there is a lack of information about video content because generating video meta-data is complex. It demands too much time to be performed by humans, and from the technology perspective, it is not easy to overcome obstacles regarding the huge amount and diversity of video frames. In this work we propose an automated face recognition system to detect and recognize humans within videos. It was developed to recognize characters,in order to increase video meta-data. It combines standard computer vision techniques to improved accuracy by processing existing models output data in a complementary manner. We evaluated the performance of the system in a real data set from a large media company.
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