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Pose estimation and tracking using multivariate regression

Abstract:
This paper presents an extension of the relevance vector machine (RVM) algorithm to multivariate regression. This allows the application to the task of estimating the pose of an articulated object from a single camera. RVMs are used to learn a one-to-many mapping from image features to state space, thereby being able to handle pose ambiguity.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.patrec.2008.02.004

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
ORCID:
0009-0006-0259-5732


Publisher:
Elsevier
Journal:
Pattern Recognition Letters More from this journal
Volume:
29
Issue:
9
Pages:
1302-1310
Publication date:
2008-02-20
Acceptance date:
2008-01-01
DOI:
ISSN:
0167-8655


Language:
English
Pubs id:
971550
Local pid:
pubs:971550
Deposit date:
2024-05-21

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