GIRAUD, Rémi; TA, Vinh-Thong; PAPADAKIS, Nicolas

Métadonnées

Licence d’utilisation du document

http://creativecommons.org/licenses/by-nc/

GIRAUD, Rémi
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Institut de Mathématiques de Bordeaux [IMB]

TA, Vinh-Thong
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Institut Polytechnique de Bordeaux [Bordeaux INP]

PAPADAKIS, Nicolas
Institut de Mathématiques de Bordeaux [IMB]

Langue

Communication dans un congrès

Ce document a été publié dans

IEEE International Conference on Image Processing (ICIP'17), 2017-09-17, Beijing. p. 3455-3459

Résumé en anglais

Regular decompositions are necessary for most superpixel-based object recognition or tracking applications. So far in the literature, the regularity or compactness of a superpixel shape is mainly measured by its circularity. In this work, we first demonstrate that such measure is not adapted for super-pixel evaluation, since it does not directly express regularity but circular appearance. Then, we propose a new metric that considers several shape regularity aspects: convexity, balanced repartition, and contour smoothness. Finally, we demonstrate that our measure is robust to scale and noise and enables to more relevantly compare superpixel methods.< Réduire

Mots clés en anglais

Superpixels

Quality measure

Compactness

URI

https://oskar-bordeaux.fr/handle/20.500.12278/193663

Project ANR

Generalized Optimal Transport Models for Image processing - ANR-16-CE33-0010

Origine

Importé de hal

Unités de recherche

Institut de Mathématiques de Bordeaux (IMB) - UMR 5251