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Measuring uncertainty in graph cut solutions

Abstract:

In recent years graph cuts have become a popular tool for performing inference in Markov and conditional random fields. In this context the question arises as to whether it might be possible to compute a measure of uncertainty associated with the graph cut solutions. In this paper we answer this particular question by showing how the min-marginals associated with the label assignments of a random field can be efficiently computed using a new algorithm based on dynamic graph cuts. The min-marg...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.cviu.2008.07.002

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
ORCID:
0009-0006-0259-5732
Publisher:
Elsevier
Journal:
Computer Vision and Image Understanding More from this journal
Volume:
112
Issue:
1
Pages:
30-38
Publication date:
2008-07-15
Acceptance date:
2008-07-02
DOI:
EISSN:
1090-235X
ISSN:
1049-9660
Language:
English
Pubs id:
971540
Local pid:
pubs:971540
Deposit date:
2024-05-21

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