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@inproceedings{Schmidt-Cremers-dagm09,
 author = {F. R. Schmidt and D. Cremers},
 title = {A Closed-Form Solution for Image Sequence Segmentation with Dynamical Shape Priors},
 booktitle = {Pattern Recognition (Proc. DAGM)},
 year = {2009},
 address = {Jena, Germany},
 month = {September},
 titleurl = {sc09.pdf},
 topic = {Shape Priors},
 keywords = {shape-priors},
}

@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},
}

@inproceedings{Schoenemann-Cremers-07a,
 author = {T. Schoenemann and D. Cremers},
 title = {Globally Optimal Image Segmentation with an Elastic Shape Prior},
 booktitle = {IEEE International Conference on Computer Vision (ICCV)},
 year = {2007},
 address = {Rio de Janeiro, Brazil},
 month = {oct},
 keywords = {shape-priors},
 titleurl = {shape_iccv07.pdf},
 topic = {Shape, Segmentation, Graph, Shape Priors},
}

@inproceedings{Cremers07,
 author = {D. Cremers},
 title = {Nonlinear Dynamical Shape Priors for Level Set Segmentation},
 booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
 year = {2007},
 titleurl = {cremers_cvpr07.pdf},
 keywords = {shape-priors},
 topic = {Level Sets, Tracking, Shape Priors, Segmentation},
}

@article{Cremers-jsc08,
 author = {D. Cremers},
 title = {Nonlinear Dynamical Shape Priors for Level Set Segmentation},
 journal = {Journal of Scientific Computing},
 volume = {35},
 number = {2-3},
 pages = {132--143},
 year = {2008},
 month = {jun},
 titleurl = {cremers_jsc08.pdf},
 keywords = {shape-priors},
 topic = {Level Sets, Tracking, Shape Priors, Segmentation},
}

@inproceedings{BBPW04,
 author = {T. Brox and A. Bruhn and N. Papenberg and J. Weickert},
 title = {High accuracy optical flow estimation based on a theory for warping},
 booktitle = {European Conference on Computer Vision (ECCV)},
 year = {2004},
 editor = {T. Pajdla and J. Matas},
 volume = {3024},
 series = {LNCS},
 pages = {25--36},
 address = {Prague, Czech Republic},
 month = {may},
 publisher = {Springer},
 award = {{<a href="http://cmp.felk.cvut.cz/eccv2004/">Received "The Longuet-Higgins
    Best Paper Award"</a>}},
 copyright = {{<a href="http://www.springer.de/comp/lncs/index.html">Springer-Verlag
    Berlin Heidelberg 2004</a>}},
 titleurl = {brox_eccv04_of.pdf},
 keywords = {shape-priors, optical-flow},
 topic = {Optic Flow, Motion},
}

@article{Cremers-06,
 author = {D. Cremers},
 title = {Dynamical statistical shape priors for level set based tracking},
 journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
 year = {2006},
 volume = {28},
 number = {8},
 pages = {1262--1273},
 month = {aug},
 keywords = {shape-priors},
 titleurl = {cremers_pami06.pdf},
 topic = {Level Sets, Shape Priors, Segmentation, Tracking},
}

@article{Brox-et-al-pami09,
 author = {T. Brox and B. Rosenhahn and J. Gall and D. Cremers},
 title = {Combined region- and motion-based 3D tracking of rigid and
                  articulated objects},
 journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
 year = {2009},
 volume = {32},
 number = {3},
 pages = {402-415},
 keywords = {tracking,shape-priors},
 titleurl = {brox_et_al_pami09.pdf},
 topic = {Level Sets, Shape Priors, 3DTracking},
}

@article{Cremers-et-al-ijcv07,
 author = {D. Cremers and M. Rousson and R. Deriche},
 title = {A review of statistical approaches to level set
                  segmentation: integrating color, texture, motion and
                  shape},
 journal = {International Journal of Computer Vision},
 year = {2007},
 volume = {72},
 number = {2},
 pages = {195--215},
 month = {apr},
 titleurl = {cremers_rousson_deriche_ijcv07.pdf},
 keywords = {shape-priors, medical imaging},
 topic = {Segmentation, Statistics, Shape Priors, Level Sets, Motion},
}

@inproceedings{Cremers-et-al-02,
 author = {D. Cremers and T. Kohlberger and C. Schnörr},
 title = {Nonlinear shape statistics in {M}umford--{S}hah based segmentation},
 booktitle = {European Conference on Computer Vision (ECCV)},
 year = {2002},
 editor = {A. Heyden and others},
 volume = {2351},
 series = {LNCS},
 pages = {93--108},
 address = {Copenhagen},
 month = {May},
 publisher = {Springer},
 titleurl = {cremers_eccv02.pdf},
 keywords = {shape-priors},
 topic = {Segmentation, Statistics, Shape Priors, Machine Learning},
}

@article{Cremers-et-al-03hd,
 author = {D. Cremers and T. Kohlberger and C. Schnörr},
 title = {Shape {S}tatistics in {K}ernel {S}pace for {V}ariational {I}mage
    {S}egmentation},
 journal = {Pattern {R}ecognition},
 year = {2003},
 volume = {36},
 pages = {1929--1943},
 number = {9},
 award = {Awarded Best Paper of the Year 2003},
 titleurl = {nonlinear_pr03.pdf},
 keywords = {shape-priors},
 topic = {Shape Priors, Statistics, Machine Learning, Segmentation},
}

@inproceedings{Cremers-et-al-04b,
 author = {D. Cremers and S. J. Osher and S. Soatto},
 title = {Kernel density estimation and intrinsic alignment for knowledge-driven
    segmentation: {T}eaching level sets to walk},
 booktitle = {Pattern Recognition (Proc. DAGM)},
 year = {2004},
 editor = {C. E. Rasmussen},
 volume = {3175},
 series = {LNCS},
 pages = {36--44},
 publisher = {Springer},
 titleurl = {cremers_dagm04.pdf},
 keywords = {shape-priors},
 topic = {Level Sets, Shape Priors, Statistics, Segmentation},
}

@incollection{Cremers-Rousson-07,
 author = {D. Cremers and M. Rousson},
 title = {Efficient kernel density estimation of shape and intensity priors
    for level set segmentation},
 booktitle = {Parametric and {G}eometric {D}eformable {M}odels: {A}n application
    in {B}iomaterials and {M}edical {I}magery},
 publisher = {Springer},
 year = {2007},
 editor = {J. S. Suri and A. Farag},
 month = {May},
 titleurl = {cremers_rousson07.pdf},
 topic = {Segmentation, Shape Priors, Medical Image Analysis, Statistics},
 keywords = {shape-priors, medical imaging},
}

@inproceedings{Cremers-et-al-dyn,
 author = {D. Cremers and C. Schnörr and J. Weickert and C. Schellewald},
 title = {Learning of translation invariant shape knowledge for steering diffusion
    snakes},
 booktitle = {Dynamische {P}erzeption},
 year = {2000},
 editor = {G. Baratoff and H. Neumann},
 volume = {9},
 series = {Proceedings on Artificial Intelligence},
 pages = {117--122},
 address = {Ulm Germany},
 month = {Nov.},
 publisher = {Infix},
 titleurl = {dynperz00.ps.gz},
 keywords = {shape-priors},
 topic = {Shape Priors, Statistics, Segmentation},
}

@inproceedings{Cremers-et-al-00,
 author = {D. Cremers and C. Schnörr and J. Weickert and C. Schellewald},
 title = {Diffusion {S}nakes using statistical shape knowledge},
 booktitle = {Algebraic {F}rames for the {P}erception-{A}ction {C}ycle},
 year = {2000},
 editor = {G. Sommer and Y.Y. Zeevi},
 volume = {1888},
 series = {LNCS},
 pages = {164--174},
 address = {Kiel, Germany},
 month = {Sept.},
 publisher = {Springer},
 titleurl = {afpac2000.ps.gz},
 keywords = {shape-priors},
 topic = {Shape Priors, Statistics, Segmentation},
}

@inproceedings{Cremers-Soatto-03b,
 author = {D. Cremers and S. Soatto},
 title = {A pseudo-distance for shape priors in level set segmentation},
 booktitle = {I{EEE} 2nd {I}nt. {W}orkshop on {V}ariational, {G}eometric and {L}evel
    {S}et {M}ethods},
 year = {2003},
 editor = {N. Paragios},
 pages = {169--176},
 address = {Nice},
 titleurl = {cremers_soatto_vlsm03.pdf},
 keywords = {shape-priors},
 topic = {Shape Priors},
}

@inproceedings{Cremers-et-al-03,
 author = {D. Cremers and N. Sochen and C. Schnörr},
 title = {Towards {R}ecognition-based {V}ariational {S}egmentation {U}sing
    {S}hape {P}riors and {D}ynamic {L}abeling},
 booktitle = {Scale-{S}pace {M}ethods in {C}omputer {V}ision},
 year = {2003},
 editor = {L. D. Griffin and M. Lillholm},
 volume = {2695},
 series = {LNCS},
 pages = {388--400},
 address = {Isle of Skye},
 publisher = {Springer},
 titleurl = {dynamic_labeling.pdf},
 keywords = {shape-priors},
 topic = {Shape Priors, Level Sets, Segmentation, Recognition},
}

@inproceedings{Cremers-et-al-04,
 author = {D. Cremers and N. Sochen and C. Schnörr},
 title = {Multiphase dynamic labeling for variational recognition-driven image
    segmentation},
 booktitle = {European Conference on Computer Vision (ECCV)},
 year = {2004},
 editor = {T. Pajdla and V. Hlavac},
 volume = {3024},
 series = {LNCS},
 pages = {74--86},
 publisher = {Springer},
 titleurl = {cremers_eccv04.pdf},
 keywords = {shape-priors},
 topic = {Shape Priors, Level Sets, Segmentation, Recognition},
}

@article{Cremers-et-al-02c,
 author = {D. Cremers and F. Tischhäuser and J. Weickert and C. Schnörr},
 title = {Diffusion {S}nakes: {I}ntroducing statistical shape knowledge into
    the {M}umford--{S}hah functional},
 journal = {International Journal of Computer Vision},
 year = {2002},
 volume = {50},
 pages = {295--313},
 number = {3},
 titleurl = {cremers_et_al_ijcv02.pdf},
 keywords = {shape-priors},
 topic = {Shape Priors, Segmentation, Statistics},
}

@inproceedings{stuehmer-et-al-iccv2013,
 author = {J. Stühmer and P. Schröder and D. Cremers},
 title = {Tree Shape Priors with Connectivity Constraints using Convex Relaxation on General Graphs},
 year = {2013},
 address = {Sydney, Australia},
 month = {December},
 titleurl = {stuehmer-et-al-iccv2013.pdf},
 booktitle = {IEEE International Conference on Computer Vision (ICCV)},
 topic = {Segmentation, Shape Priors},
 keywords = {Convex-Relaxation, Segmentation, shape-priors, medical imaging},
 award = {Oral Presentation},
}

@inproceedings{Stuehmer-Cremers-emmcvpr15,
 author = {J. Stühmer and D. Cremers},
 title = {A Fast Projection Method for Connectivity Constraints in Image Segmentation},
 booktitle = {Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR)},
 editor = {X.-C. Tai and E. Bae and T. F. Chan and M. Lysaker},
 series = {LNCS},
 year = {2015},
 keywords = {image-segmentation,constrained convex optimization,shape-priors,medical imaging},
 topic = {Segmentation, Shape Priors},
}