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Journal article

Real-time tracking of single and multiple objects from depth-colour imagery Using 3D signed distance functions

Abstract:

We describe a novel probabilistic framework for real-time tracking of multiple objects from combined depthcolour imagery. Object shape is represented implicitly using 3D signed distance functions. Probabilistic generative models based on these functions are developed to account for the observed RGB-D imagery, and tracking is posed as a maximum a posteriori problem. We present first a method suited to tracking a single rigid 3D object, and then generalise this to multiple objects by combining ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/s11263-016-0978-2

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Institution:
University of Oxford
Oxford college:
St Anne's College
Role:
Author
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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
Publisher:
Springer Publisher's website
Journal:
International Journal of Computer Vision Journal website
Publication date:
2017-01-01
Acceptance date:
2016-11-29
DOI:
ISSN:
1573-1405 and 0920-5691
Source identifiers:
672416
Keywords:
Pubs id:
pubs:672416
UUID:
uuid:72b8e1a7-3e71-4b9e-b8e9-fa03bf744dbd
Local pid:
pubs:672416
Deposit date:
2017-01-24

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