Half-integrality based algorithms for cosegmentation of images
We study the cosegmentation problem where the objective is to segment the same object (i.e., region) from a pair of images. The segmentation for each image can be cast using a partitioning/segmentation function with an additional constraint that seeks to make the histograms of the segmented regions...
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| Veröffentlicht in: | 2009 IEEE Conference on Computer Vision and Pattern Recognition S. 2028 - 2035 |
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| Hauptverfasser: | , , |
| Format: | Tagungsbericht Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
United States
IEEE
01.01.2009
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| Schlagworte: | |
| ISBN: | 1424439922, 9781424439928 |
| ISSN: | 1063-6919, 1063-6919 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | We study the cosegmentation problem where the objective is to segment the same object (i.e., region) from a pair of images. The segmentation for each image can be cast using a partitioning/segmentation function with an additional constraint that seeks to make the histograms of the segmented regions (based on intensity and texture features) similar. Using Markov random field (MRF) energy terms for the simultaneous segmentation of the images together with histogram consistency requirements using the squared L 2 (rather than L 1 ) distance, after linearization and adjustments, yields an optimization model with some interesting combinatorial properties. We discuss these properties which are closely related to certain relaxation strategies recently introduced in computer vision. Finally, we show experimental results of the proposed approach. |
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| Bibliographie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISBN: | 1424439922 9781424439928 |
| ISSN: | 1063-6919 1063-6919 |
| DOI: | 10.1109/CVPR.2009.5206652 |