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"Here's looking at you, kid." Detecting people looking at each other in videos

Abstract:
The objective of this work is to determine if people are interacting in TV video by detecting whether they are looking at each other or not. We determine both the temporal period of the interaction and also spatially localize the relevant people. We make the following three contributions: (i) head pose estimation in unconstrained scenarios (TV video) using Gaussian Process regression; (ii) propose and evaluate several methods for assessing whether and when pairs of people are looking at each other in a video shot; and (iii) introduce new ground truth annotation for this task, extending the TV Human Interactions Dataset [22]. The peformance of the methods is evaluated on this dataset, which consists of 300 video clips extracted from TV shows. Despite the variety and difficulty of this video material, our best method obtains an average precision of 86.2%.
Publication status:
Published
Peer review status:
Peer reviewed

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Publication website:
https://bmva-archive.org.uk/bmvc/2011/proceedings/paper22/index.html

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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/0472cxd90
Grant:
228180
Programme:
VisRec


Publisher:
British Machine Vision Association
Host title:
Proceedings of the British Machine Vision Conference 2011
Pages:
22.1-22.12
Publication date:
2011-10-11
Acceptance date:
2011-06-28
Event title:
22nd British Machine Vision Conference (BMVC 2011)
Event location:
Dundee, Scotland
Event website:
https://bmva-archive.org.uk/bmvc/2011/index.html
Event start date:
2011-08-29
Event end date:
2011-09-02
EISBN:
190172543X


Language:
English
Pubs id:
1172387
Local pid:
pubs:1172387
Deposit date:
2024-07-22

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