Spatio-Temporal Video Segmentation with Shape Growth or Shrinkage Constraint - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Article Dans Une Revue IEEE Transactions on Image Processing Année : 2014

Spatio-Temporal Video Segmentation with Shape Growth or Shrinkage Constraint

Résumé

We propose a new method for joint segmentation of monotonously growing or shrinking shapes in a time sequence of noisy images. The task of segmenting the image time series is expressed as an optimization problem using the spatio-temporal graph of pixels, in which we are able to impose the constraint of shape growth or of shrinkage by introducing monodirectional infinite links connecting pixels at the same spatial locations in successive image frames. The globally-optimal solution is computed with a graph cut. The performance of the proposed method is validated on three applications: segmentation of melting sea ice floes and of growing burned areas from time series of 2D satellite images, and segmentation of a growing brain tumor from sequences of 3D medical scans. In the latter application, we impose an additional inter-sequences inclusion constraint by adding directed infinite links between pixels of dependent image structures.
Fichier principal
Vignette du fichier
2014_IEEETIP_Tarabalka.pdf (6 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01052543 , version 1 (28-07-2014)

Identifiants

  • HAL Id : hal-01052543 , version 1

Citer

Yuliya Tarabalka, Guillaume Charpiat, Ludovic Brucker, Bjoern Menze. Spatio-Temporal Video Segmentation with Shape Growth or Shrinkage Constraint. IEEE Transactions on Image Processing, 2014, 23 (9), pp.3829-3840. ⟨hal-01052543⟩

Collections

INRIA INRIA2
287 Consultations
428 Téléchargements

Partager

Gmail Facebook X LinkedIn More