Geodesic star convexity for interactive image segmentation

@article{Gulshan2010GeodesicSC,
  title={Geodesic star convexity for interactive image segmentation},
  author={Varun Gulshan and Carsten Rother and Antonio Criminisi and Andrew Blake and Andrew Zisserman},
  journal={2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition},
  year={2010},
  pages={3129-3136}
}
In this paper we introduce a new shape constraint for interactive image segmentation. It is an extension of Veksler's [25] star-convexity prior, in two ways: from a single star to multiple stars and from Euclidean rays to Geodesic paths. Global minima of the energy function are obtained subject to these new constraints. We also introduce Geodesic Forests, which exploit the structure of shortest paths in implementing the extended constraints. The star-convexity prior is used here in an… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 235 CITATIONS

Minimisation du risque empirique avec des fonctions de perte nonmodulaires

VIEW 6 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

Fine-structured object segmentation via neighborhood propagation

  • Pattern Recognition
  • 2016
VIEW 8 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

Predicting Sufficient Annotation Strength for Interactive Foreground Segmentation

  • 2013 IEEE International Conference on Computer Vision
  • 2013
VIEW 11 EXCERPTS
CITES METHODS
HIGHLY INFLUENCED

Click Carving: Interactive Object Segmentation in Images and Videos with Point Clicks

  • International Journal of Computer Vision
  • 2019
VIEW 16 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

Temporally Coherent General Dynamic Scene Reconstruction

VIEW 6 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

On the Stability of the K-Max Distance to the Position of Seeds

  • 2018 25th IEEE International Conference on Image Processing (ICIP)
  • 2018
VIEW 5 EXCERPTS
CITES METHODS
HIGHLY INFLUENCED

SeedNet: Automatic Seed Generation with Deep Reinforcement Learning for Robust Interactive Segmentation

  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
  • 2018
VIEW 6 EXCERPTS
CITES METHODS
HIGHLY INFLUENCED

FILTER CITATIONS BY YEAR

2001
2019

CITATION STATISTICS

  • 67 Highly Influenced Citations

  • Averaged 23 Citations per year from 2017 through 2019

References

Publications referenced by this paper.
SHOWING 1-10 OF 25 REFERENCES

Geodesic Matting: A Framework for Fast Interactive Image and Video Segmentation and Matting

  • International Journal of Computer Vision
  • 2008
VIEW 6 EXCERPTS
HIGHLY INFLUENTIAL

Star Shape Prior for Graph-Cut Image Segmentation

  • ECCV
  • 2008
VIEW 10 EXCERPTS
HIGHLY INFLUENTIAL

Global connectivity potentials for random field models

  • 2009 IEEE Conference on Computer Vision and Pattern Recognition
  • 2009
VIEW 1 EXCERPT

Paint selection

VIEW 2 EXCERPTS

and A

M. Everingham, L. Van Gool, C.K.I. Williams, J. Winn
  • Zisserman. The PASCAL Visual Object Classes Challenge 2009
  • 2009
VIEW 3 EXCERPTS