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231224s2017 xx |||||o 00| ||eng c |
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|a 10.1109/TPAMI.2016.2554550
|2 doi
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|a pubmed24n0865.xml
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|a eng
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| 100 |
1 |
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|a Xu, Yongchao
|e verfasserin
|4 aut
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| 245 |
1 |
0 |
|a Hierarchical Segmentation Using Tree-Based Shape Spaces
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| 264 |
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|c 2017
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| 336 |
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
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|2 rdamedia
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| 338 |
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|a ƒa Online-Ressource
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|2 rdacarrier
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| 500 |
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|a Date Completed 20.09.2018
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| 500 |
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|a Date Revised 20.09.2018
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a Current trends in image segmentation are to compute a hierarchy of image segmentations from fine to coarse. A classical approach to obtain a single meaningful image partition from a given hierarchy is to cut it in an optimal way, following the seminal approach of the scale-set theory. While interesting in many cases, the resulting segmentation, being a non-horizontal cut, is limited by the structure of the hierarchy. In this paper, we propose a novel approach that acts by transforming an input hierarchy into a new saliency map. It relies on the notion of shape space: a graph representation of a set of regions extracted from the image. Each region is characterized with an attribute describing it. We weigh the boundaries of a subset of meaningful regions (local minima) in the shape space by extinction values based on the attribute. This extinction-based saliency map represents a new hierarchy of segmentations highlighting regions having some specific characteristics. Each threshold of this map represents a segmentation which is generally different from any cut of the original hierarchy. This new approach thus enlarges the set of possible partition results that can be extracted from a given hierarchy. Qualitative and quantitative illustrations demonstrate the usefulness of the proposed method
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| 650 |
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4 |
|a Journal Article
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| 700 |
1 |
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|a Carlinet, Edwin
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Geraud, Thierry
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Najman, Laurent
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 39(2017), 3 vom: 20. März, Seite 457-469
|w (DE-627)NLM098212257
|x 1939-3539
|7 nnns
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| 773 |
1 |
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|g volume:39
|g year:2017
|g number:3
|g day:20
|g month:03
|g pages:457-469
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| 856 |
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|u http://dx.doi.org/10.1109/TPAMI.2016.2554550
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