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Automated video labelling: identifying faces by corroborative evidence

Abstract:

We present a method for automatically labelling all faces in video archives, such as TV broadcasts, by combining multiple evidence sources and multiple modalities (visual and audio). We target the problem of ever-growing online video archives, where an effective, scalable indexing solution cannot require a user to provide manual annotation or supervision. To this end, we make three key contributions: (1) We provide a novel, simple, method for determining if a person is famous or not using ima...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/MIPR51284.2021.00019

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
ORCID:
0000-0002-8945-8573
Publisher:
IEEE Publisher's website
Pages:
77-83
Host title:
Proceedings of the 2021 International Conference on Multimedia Information Processing and Retrieval
Publication date:
2021-10-19
Acceptance date:
2020-12-18
Event title:
International Conference on Multimedia Information Processing and Retrieval, 2021
Event location:
Tokyo, Japan
Event website:
https://mipr2021.org/
Event start date:
2021-09-08T00:00:00Z
Event end date:
2021-09-10T00:00:00Z
DOI:
EISBN:
978-1-6654-1865-2
ISBN:
978-1-6654-4814-7
Language:
English
Keywords:
Pubs id:
1163224
Local pid:
pubs:1163224
Deposit date:
2021-02-23

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