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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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Department:
St Annes College
Kähler, O More by this author
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Department:
Oxford, MPLS, Engineering Science
Publisher:
Springer Publisher's website
Journal:
International Journal of Computer Vision Journal website
Publication date:
2017-01-05
Acceptance date:
2016-11-29
DOI:
ISSN:
0920-5691 and 1573-1405
Pubs id:
pubs:672416
URN:
uri:72b8e1a7-3e71-4b9e-b8e9-fa03bf744dbd
UUID:
uuid:72b8e1a7-3e71-4b9e-b8e9-fa03bf744dbd
Local pid:
pubs:672416

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