SuperPatchMatch: an Algorithm for Robust Correspondences using Superpixel Patches
| hal.structure.identifier | Laboratoire Bordelais de Recherche en Informatique [LaBRI] | |
| hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
| dc.contributor.author | GIRAUD, Rémi | |
| hal.structure.identifier | Institut Polytechnique de Bordeaux [Bordeaux INP] | |
| hal.structure.identifier | Laboratoire Bordelais de Recherche en Informatique [LaBRI] | |
| dc.contributor.author | TA, Vinh-Thong | |
| hal.structure.identifier | Laboratoire Bordelais de Recherche en Informatique [LaBRI] | |
| dc.contributor.author | BUGEAU, Aurélie | |
| hal.structure.identifier | Laboratoire Bordelais de Recherche en Informatique [LaBRI] | |
| dc.contributor.author | COUPÉ, Pierrick | |
| hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
| dc.contributor.author | PAPADAKIS, Nicolas | |
| dc.date.accessioned | 2024-04-04T03:09:59Z | |
| dc.date.available | 2024-04-04T03:09:59Z | |
| dc.date.issued | 2017 | |
| dc.identifier.issn | 1057-7149 | |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/193655 | |
| dc.description.abstractEn | Superpixels have become very popular in many computer vision applications. Nevertheless, they remain underexploited since the superpixel decomposition may produce irregular and non stable segmentation results due to the dependency to the image content. In this paper, we first introduce a novel structure, a superpixel-based patch, called SuperPatch. The proposed structure, based on superpixel neighborhood, leads to a robust descriptor since spatial information is naturally included. The generalization of the PatchMatch method to SuperPatches, named SuperPatchMatch, is introduced. Finally, we propose a framework to perform fast segmentation and labeling from an image database, and demonstrate the potential of our approach since we outperform, in terms of computational cost and accuracy, the results of state-of-the-art methods on both face labeling and medical image segmentation. | |
| dc.description.sponsorship | Generalized Optimal Transport Models for Image processing - ANR-16-CE33-0010 | |
| dc.language.iso | en | |
| dc.publisher | Institute of Electrical and Electronics Engineers | |
| dc.subject.en | Patch-based method | |
| dc.subject.en | PatchMatch | |
| dc.subject.en | Labeling | |
| dc.subject.en | Superpixels | |
| dc.subject.en | Segmentation | |
| dc.title.en | SuperPatchMatch: an Algorithm for Robust Correspondences using Superpixel Patches | |
| dc.type | Article de revue | |
| dc.identifier.doi | 10.1109/TIP.2017.2708504 | |
| dc.subject.hal | Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV] | |
| dc.subject.hal | Informatique [cs]/Imagerie médicale | |
| dc.subject.hal | Informatique [cs]/Traitement des images | |
| bordeaux.journal | IEEE Transactions on Image Processing | |
| bordeaux.hal.laboratories | Institut de Mathématiques de Bordeaux (IMB) - UMR 5251 | * |
| bordeaux.institution | Université de Bordeaux | |
| bordeaux.institution | Bordeaux INP | |
| bordeaux.institution | CNRS | |
| bordeaux.peerReviewed | oui | |
| hal.identifier | hal-01432116 | |
| hal.version | 3 | |
| hal.popular | non | |
| hal.audience | Internationale | |
| hal.origin.link | https://hal.archives-ouvertes.fr//hal-01432116v3 | |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=IEEE%20Transactions%20on%20Image%20Processing&rft.date=2017&rft.eissn=1057-7149&rft.issn=1057-7149&rft.au=GIRAUD,%20R%C3%A9mi&TA,%20Vinh-Thong&BUGEAU,%20Aur%C3%A9lie&COUP%C3%89,%20Pierrick&PAPADAKIS,%20Nicolas&rft.genre=article |
Files in this item
| Files | Size | Format | View |
|---|---|---|---|
|
There are no files associated with this item. |
|||