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Learning to track the visual motion of contours

Abstract:
A development of a method for tracking visual contours is described. Given an “untrained” tracker, a training motion of an object can be observed over some extended time and stored as an image sequence. The image sequence is used to learn parameters in a stochastic differential equation model. These are used, in turn, to build a tracker whose predictor imitates the motion in the training set. Tests show that the resulting trackers can be markedly tuned to desired curve shapes and classes of motions.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/0004-3702(95)00032-1

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author


Publisher:
Elsevier
Journal:
Artificial Intelligence More from this journal
Volume:
78
Issue:
1–2
Pages:
179–212
Publication date:
1995-10-01
Edition:
Publisher's version
DOI:
ISSN:
0004-3702


Language:
English
Keywords:
Subjects:
UUID:
uuid:f23386fd-29de-4e5e-9cb5-342f4e40453d
Local pid:
ora:8096
Deposit date:
2014-02-25
ARK identifier:

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