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Shape Priors in Variational Image Segmentation: Convexity, Lipschitz Continuity and Globally Optimal Solutions (bibtex)
Shape Priors in Variational Image Segmentation: Convexity, Lipschitz Continuity and Globally Optimal Solutions (bibtex)
by D. Cremers, F. R. Schmidt and F. Barthel
Reference:
Shape Priors in Variational Image Segmentation: Convexity, Lipschitz Continuity and Globally Optimal Solutions (D. Cremers, F. R. Schmidt and F. Barthel), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008. 
Bibtex Entry:
@string{cvpr="IEEE Conference on Computer Vision and Pattern Recognition (CVPR)"}
@inproceedings{Cremers-et-al-cvpr08,
 author = {D. Cremers and F. R. Schmidt and F. Barthel},
 title = {Shape Priors in Variational Image Segmentation: Convexity, Lipschitz Continuity and Globally Optimal Solutions},
 booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
 year = {2008},
 address = {Anchorage, Alaska},
 month = {jun},
 keywords = {shape-priors, convex-relaxation},
 titleurl = {cremers_et_al_cvpr08.pdf},
 topic = {Shape Priors, Convex Relaxation Methods},
}
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