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OPTIC FLOW SEGMENTATION AS AN ILL-POSED AND MAXIMUM-LIKELIHOOD PROBLEM

Abstract:

It is shown how the segmentation problem encountered in the interpretation of visual motion, for example, may be formulated as an ill-posed problem using the notion of maximum likelihood to provide a general framework and guide the choice of regularizing constraints. The statistical consequences of the segmentation procedure proposed are examined and it is shown how the notion of maximum likelihood leads to a natural way of estimating parameters in the optimization function, especially the no...

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Publication status:
Published

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Journal:
IMAGE AND VISION COMPUTING More from this journal
Volume:
3
Issue:
4
Pages:
163-169
Publication date:
1985-11-01
DOI:
ISSN:
0262-8856
Language:
English
Keywords:
Pubs id:
pubs:315775
UUID:
uuid:077487fa-ca41-4a3b-a21b-889cbc880a18
Local pid:
pubs:315775
Source identifiers:
315775
Deposit date:
2012-12-19

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