Spatio-temporal video segmentation with shape growth or shrinkage constraint

Yuliya Tarabalka, Guillaume Charpiat, Ludovic Brucker, Bjoern H. Menze

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

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 intersequences inclusion constraint by adding directed infinite links between pixels of dependent image structures.

Original languageEnglish
Article number6850066
Pages (from-to)3829-3840
Number of pages12
JournalIEEE Transactions on Image Processing
Volume23
Issue number9
DOIs
StatePublished - Sep 2014

Keywords

  • Video segmentation
  • energy minimization
  • graph cut
  • infinite links
  • shape growth

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