Texture-Aware Superpixel Segmentation
| hal.structure.identifier | Laboratoire de l'intégration, du matériau au système [IMS] | |
| hal.structure.identifier | Institut Polytechnique de Bordeaux [Bordeaux INP] | |
| dc.contributor.author | GIRAUD, Rémi | |
| hal.structure.identifier | Laboratoire Bordelais de Recherche en Informatique [LaBRI] | |
| hal.structure.identifier | Institut Polytechnique de Bordeaux [Bordeaux INP] | |
| dc.contributor.author | TA, Vinh-Thong | |
| hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
| dc.contributor.author | PAPADAKIS, Nicolas | |
| hal.structure.identifier | Laboratoire de l'intégration, du matériau au système [IMS] | |
| dc.contributor.author | BERTHOUMIEU, Yannick | |
| dc.contributor.editor | IEEE | |
| dc.date.accessioned | 2024-04-04T03:00:23Z | |
| dc.date.available | 2024-04-04T03:00:23Z | |
| dc.date.issued | 2019-08-23 | |
| dc.date.conference | 2019-09-28 | |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/192813 | |
| dc.description.abstractEn | Most superpixel algorithms compute a trade-off between spatial and color features at the pixel level. Hence, they may need fine parameter tuning to balance the two measures, and highly fail to group pixels with similar local texture properties. In this paper, we address these issues with a new Texture-Aware SuperPixel (TASP) method. To accurately segment textured and smooth areas, TASP automatically adjusts its spatial constraint according to the local feature variance. Then, to ensure texture homogeneity within superpixels, a new pixel to superpixel patch-based distance is proposed. TASP outperforms the segmentation accuracy of the state-of-the-art methods on texture and also natural color image datasets. | |
| dc.language.iso | en | |
| dc.title.en | Texture-Aware Superpixel Segmentation | |
| dc.type | Communication dans un congrès | |
| dc.subject.hal | Informatique [cs]/Traitement du signal et de l'image | |
| dc.description.sponsorshipEurope | Nonlocal Methods for Arbitrary Data Sources | |
| bordeaux.page | 1465-1469 | |
| bordeaux.hal.laboratories | Institut de Mathématiques de Bordeaux (IMB) - UMR 5251 | * |
| bordeaux.institution | Université de Bordeaux | |
| bordeaux.institution | Bordeaux INP | |
| bordeaux.institution | CNRS | |
| bordeaux.conference.title | IEEE International Conference on Image Processing (ICIP'19) | |
| bordeaux.country | TW | |
| bordeaux.conference.city | Taipei | |
| bordeaux.peerReviewed | oui | |
| hal.identifier | hal-01995819 | |
| hal.version | 2 | |
| hal.invited | non | |
| hal.proceedings | oui | |
| hal.popular | non | |
| hal.audience | Internationale | |
| hal.origin.link | https://hal.archives-ouvertes.fr//hal-01995819v2 | |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.date=2019-08-23&rft.spage=1465-1469&rft.epage=1465-1469&rft.au=GIRAUD,%20R%C3%A9mi&TA,%20Vinh-Thong&PAPADAKIS,%20Nicolas&BERTHOUMIEU,%20Yannick&rft.genre=unknown |
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