% generated by bibtexbrowser % % Encoding: UTF-8 @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 = {{Received "The Longuet-Higgins Best Paper Award"}}, copyright = {{Springer-Verlag Berlin Heidelberg 2004}}, 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}, }