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Automated visual identification of characters in situation comedies

Abstract:
The objectives of the work described in this paper are simply stated: given examples of a particular person and an unlabelled video, we wish to find every instance of that person in the video and in others. This is an extremely difficult problem because of the many sources of variation in the person's appearance. We present a two stage approach. A 3-D ellipsoid approximation of the person's head is used to train a set of generative parts-based 'constellation' models which propose candidate detections in an image. The detected parts are then used to align the model, and the detections verified by global appearance. Novel aspects of the approach include the minimal supervision required and the generalization across a wide range of pose. We demonstrate results of detecting three characters in a TV situation comedy.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/ICPR.2004.1333938

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
Brasenose College
Role:
Author
ORCID:
0000-0002-8945-8573


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Funder identifier:
https://ror.org/00k4n6c32


Publisher:
IEEE
Host title:
Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.
Pages:
983-986
Publication date:
2004-01-01
Event title:
17th International Conference on Pattern Recognition, 2004 (ICPR 2004)
Event location:
Cambridge
Event website:
https://www.computer.org/csdl/proceedings/icpr/2004/12OmNscfI2G
Event start date:
2004-08-23
Event end date:
2004-08-26
DOI:
ISSN:
1051-4651
ISBN:
0-7695-2128-2


Language:
English
Keywords:
Pubs id:
61911
Local pid:
pubs:61911
Deposit date:
2024-10-15

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