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 Schn\'f6rr,  (2020). Assignment Flows. Handbook of Variational Methods for Nonlinear Geometric Data. Springer. 235?260. https://www.springer.com/gp/book/9783030313500\par \par  Zern, A, Zeilmann, A and Schn\'f6rr, C (2020). Assignment Flows for Data Labeling on Graphs: Convergence and Stability. preprint: arXiv. https://arxiv.org/abs/2002.11571\par \par  Zeilmann, A, Savarino, F, Petra, S and Schn\'f6rr, C (2020). Geometric Numerical Integration of the Assignment Flow. Inverse Problems. 36 034004 (33pp)\par \par  Desana, M and Schn\'f6rr, C (2020). Sum-Product Graphical Models. Machine Learning. 109 135?173\par \par  Censor, Y, Petra, S and Schn\'f6rr, C (2020). Superiorization vs. Accelerated Convex Optimization: The Superiorized/Regularized Least Squares Case. J. Appl. Numer. Optimization (in press; arXiv:1911.05498). 2 15-62. http://jano.biemdas.com/archives/1060\par \par  Zern, A, Zisler, M, Petra, S and Schn\'f6rr, C (2020). Unsupervised Assignment Flow: Label Learning on Feature Manifolds by Spatially Regularized Geometric Assignment. Journal of Mathematical Imaging and Vision. https://doi.org/10.1007/s10851-019-00935-7\par \par  Schn\'f6rr,  (2019). Assignment Flows. Variational Methods for Nonlinear Geometric Data and Applications. Springer\par \par  Savarino, F and Schn\'f6rr, C (2019). Continuous-Domain Assignment Flows. preprint: arXiv. https://arxiv.org/abs/1910.07287\par \par  Rathke, F and Schn\'f6rr, C (2019). Fast Multivariate Log-Concave Density Estimation. Comp. Statistics & Data Analysis. 140 41?58\par \par  Zeilmann, A, Savarino, F, Petra, S and Schn\'f6rr, C (2019). Geometric Numerical Integration of the Assignment Flow. Inverse Problems. https://doi.org/10.1088/1361-6420/ab2772\par \par  Kostrykin, L, Schn\'f6rr, C and Rohr, K (2019). Globally Optimal Segmentation of Cell Nuclei in Fluoroscence Microscopy Images using Shape and Intensity Information. Medical Image Analysis. https://doi.org/10.1016/j.media.2019.101536\par \par  H\'fchnerbein, R, Savarino, F, Petra, S and Schn\'f6rr, C (2019). Learning Adaptive Regularization for Image Labeling Using Geometric Assignment. Proc. SSVM. Springer\par \par  H\'fchnerbein, R, Savarino, F, Petra, S and Schn\'f6rr, C (2019). Learning Adaptive Regularization for Image Labeling Using Geometric Assignment. preprint: arXiv. https://arxiv.org/abs/1910.09976\par \par  Zisler, M, Zern, A, Petra, S and Schn\'f6rr, C (2019). Self-Assignment Flows for Unsupervised Data Labeling on Graphs. preprint: arXiv. https://arxiv.org/abs/1911.03472\par \par  Desana, M and Schn\'f6rr, C (2019). Sum-Product Graphical Models. Machine Learning. https://doi.org/10.1007/s10994-019-05813-2\par \par  Censor, Y, Petra, S and Schn\'f6rr, C (2019). Superiorization vs. Accelerated Convex Optimization: The Superiorized/Regularized Least Squares Case. preprint: arXiv. https://arxiv.org/abs/1911.05498\par \par  Zern, A, Zisler, M, Petra, S and Schn\'f6rr, C (2019). Unsupervised Assignment Flow: Label Learning on Feature Manifolds by Spatially Regularized Geometric Assignment. preprint: arXiv. https://arxiv.org/abs/1904.10863\par \par  Zisler, M, Zern, A, Petra, S and Schn\'f6rr, C (2019). Unsupervised Labeling by Geometric and Spatially Regularized Self-Assignment. Proc. SSVM. Springer\par \par  Savarino, F and Schn\'f6rr, C (2019). A Variational Perspective on the Assignment Flow. Proc. SSVM. Springer\par \par  Rathke, F and Schn\'f6rr, C (2018). Fast Multivariate Log-Concave Density Estimation. preprint: arXiv. https://arxiv.org/pdf/1805.07272.pdf\par \par  Zern, A, Rohr, K and Schn\'f6rr, C (2018). Geometric Image Labeling with Global Convex Labeling Constraints. EMMCVPR. 10746 533?547\par \par  Zeilmann, A, Savarino, F, Petra, S and Schn\'f6rr, C (2018). Geometric Numerical Integration of the Assignment Flow. preprint: arXiv. https://arxiv.org/abs/1810.06970\par \par  H\'fchnerbein, R, Savarino, F, Astr\'f6m, F and Schn\'f6rr, C (2018). Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment. SIAM J. Imaging Science. 11 1317?1362. https://epubs.siam.org/doi/abs/10.1137/17M1150669\par \par  Kostrykin, L, Schn\'f6rr, C and Rohr, K (2018). Segmentation of Cell Nuclei Using Intensity-Based Model Fitting and Sequential Convex Programming. Proc. ISBI\par \par  Zern, A, Zisler, M, Astr\'f6m, F, Petra, S and Schn\'f6rr, C (2018). Unsupervised Label Learning on Manifolds by Spatially Regularized Geometric Assignment. GCPR\par \par  Dalitz, R, Petra, S and Schn\'f6rr, C (2017). Compressed Motion Sensing. Proc. SSVM. Springer. 10302\par \par  Astr\'f6m, F and Schn\'f6rr, C (2017). A Geometric Approach for Color Image Regularization. Comp. Vision Image Understanding. 165 43?59. https://doi.org/10.1016/j.cviu.2017.10.013\par \par  Zern, A, Rohr, K and Schn\'f6rr, C (2017). Geometric Image Labeling with Global Convex Labeling Constraints. Proc. EMMCVPR\par \par  Zisler, M, Savarino, F, Petra, S and Schn\'f6rr, C (2017). Gradient Flows on a Riemannian Submanifold for Discrete Tomography. Proc. GCPR\par \par  H\'fchnerbein, R, Savarino, F, Astr\'f6m, F and Schn\'f6rr, C (2017). Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment. http://arxiv.org/abs/1710.01493\par \par  Astr\'f6m, F, Petra, S, Schmitzer, B and Schn\'f6rr, C (2017). Image Labeling by Assignment. J. Math. Imag. Vision. 58 211?238. Papers/Astroem2017.pdf\par \par  Zisler, M, Astr\'f6m, F, Petra, S and Schn\'f6rr, C (2017). Image Reconstruction by Multilabel Propagation. Proc. SSVM. Springer. 10302\par \par  Bodnariuc, E, Petra, S, Schn\'f6rr, C and Voorneveld, J (2017). A Local Spatio-Temporal Approach to Plane Wave Ultrasound Particle Image Velocimetry. Proc. GCPR\par \par  Rathke, F, Desana, M and Schn\'f6rr, C (2017). Locally Adaptive Probabilistic Models for Global Segmentation of Pathological OCT Scans. Proc. MICCAI\par \par  Astr\'f6m, F, H\'fchnerbein, R, Savarino, F, Recknagel, J and Schn\'f6rr, C (2017). MAP Image Labeling Using Wasserstein Messages and Geometric Assignment. Proc. SSVM. Springer. 10302\par \par  Savarino, F, H\'fchnerbein, R, Astr\'f6m, F, Recknagel, J and Schn\'f6rr, C (2017). Numerical Integration of Riemannian Gradient Flows for Image Labeling. Proc. SSVM. Springer. 10302\par \par  Berger, J, Lenzen, F, Becker, F, Neufeld, A and Schn\'f6rr, C (2017). \{Second-Order Recursive Filtering on the Rigid-Motion Lie Group SE(3) Based on Nonlinear Observations. J. Math. Imag. Vision. 58 102?129\par \par  Markowsky, P, Reith, S, Zuber, T E, K\'f6nig, R, Rohr, K and Schn\'f6rr, C (2017). Segmentation of cell structure using model-based set covering with iterative reweighting. Proc. ISBI\par \par  Astr\'f6m, F, Petra, S, Schmitzer, B and Schn\'f6rr, C (2016). The Assignment Manifold: A Smooth Model for Image Labeling. Proc. 2nd Int. Workshop on Differential Geometry in Computer Vision and Machine Learning (DIFF-CVML'16; oral presentation; Grenander best paper award)\par \par  Astr\'f6m, F and Schn\'f6rr, C (2016). Double-Opponent Vectorial Total Variation. Proc. ECCV\par \par  Desana, M and Schn\'f6rr, C (2016). Expectation Maximization for Sum-Product Networks as Exponential Family Mixture Models. http://arxiv.org/abs/1604.07243\par \par  Astr\'f6m, F and Schn\'f6rr, C (2016). A Geometric Approach to Color Image Regularization. https://arxiv.org/abs/1605.05977\par \par  Astr\'f6m, F, Petra, S, Schmitzer, B and Schn\'f6rr, C (2016). A Geometric Approach to Image Labeling. Proc. ECCV\par \par  Kappes, J, Speth, M, Reinelt, G and Schn\'f6rr, C (2016). Higher-order Segmentation via Multicuts. Comp. Vision Image Understanding. 143 104?119\par \par  Astr\'f6m, F, Petra, S, Schmitzer, B and Schn\'f6rr, C (2016). Image Labeling by Assignment. http://arxiv.org/abs/1603.05285\par \par  Censor, Y, Gibali, A, Lenzen, F and Schn\'f6rr, C (2016). The Implicit Convex Feasibility Problem and Its Application to Adaptive Image Denoising. J. Comp. Math. 34 608-623\par \par  Kappes, J H, Swoboda, P, Savchynskyy, B, Hazan, T and Schn\'f6rr, C (2016). Multicuts and Perturb & MAP for Probabilistic Graph Clustering. J. Math. Imag. Vision. 56 221?237\par \par  Bodnariuc, E, Petra, S, Poelma, C and Schn\'f6rr, C (2016). Parametric Dictionary-Based Velocimetry for Echo PIV. Proc. CGPR\par \par  Swoboda, P, Shekhovtsov, A, Kappes, J H, Schn\'f6rr, C and Savchynskyy, B (2016). Partial Optimality by Pruning for MAP-Inference with General Graphical Models. IEEE Trans. Patt. Anal. Mach. Intell. 38 1370?1382\par \par  Silvestri, F, Reinelt, G and Schn\'f6rr, C (2016). Symmetry-free SDP Relaxations for Affine Subspace Clustering. http://arxiv.org/abs/1607.07387\par \par  Schmitzer, B and Schn\'f6rr, C (2015). Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein Modes. J. Math. Imag. Vision. 52 436?458. http://link.springer.com/article/10.1007/s10851-014-0546-8\par \par  Kappes, J, Swoboda, P, Savchynskyy, B, Hazan, T and Schn\'f6rr, C (2015). Probabilistic Correlation Clustering and Image Partitioning Using Perturbed Multicuts. Proc. SSVM. Springer\par \par  Didden, E - M, Thorarinsdottir, T L, Lenkoski, A and Schn\'f6rr, C (2015). Shape from Texture using Locally Scaled Point Processes. Image Anal. Stereol. 34 161-170\par \par  Kappes, J H, Petra, S, Schn\'f6rr, C and Zisler, M (2015). TomoGC: Binary Tomography by Constrained Graph Cuts. Proc. GCPR\par \par  Rathke, F, Schmidt, S and Schn\'f6rr, C (2014). Probabilistic Intra-Retinal Layer Segmentation in 3-D OCT Images Using Global Shape Regularization. Medical Image Analysis. 18 781-794\par \par  Lenzen, F, Lellmann, J, Becker, F and Schn\'f6rr, C (2014). Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets. SIAM J. Imag. Sci. 7 2139?2174\par \par  Petra, S, Schn\'f6rr, C and Schr\'f6der, A (2012). Critical Parameter Values and Reconstruction Properties of Discrete Tomography: Application to Experimental Fluid Dynamics. http://arxiv.org/abs/1209.4316\par \par  Lellmann, J and Schn\'f6rr, C (2011). Continuous Multiclass Labeling Approaches and Algorithms. CoRR. abs/1102.5448. http://arxiv.org/abs/1102.5448\par \par  Nicola, A, Petra, S, Popa, C and Schn\'f6rr, C (2011). A general extending and constraining procedure for linear iterative methods. Int. J. Comp. Math. http://dx.doi.org/10.1080/00207160.2011.634002\par \par  Lellmann, J and Schn\'f6rr, C (2011). Regularizers for Vector-Valued Data and Labeling Problems in Image Processing. Control Systems and Computers. 2 43?54\par \par  Savchynskyy, B, Kappes, J H, Schmidt, S and Schn\'f6rr, C (2011). A Study of Nesterov's Scheme for Lagrangian Decomposition and MAP Labeling. IEEE International Conference on Computer Vision and Pattern Recognition (CVPR)\par \par  Lellmann, J and Schn\'f6rr, C (2010). Continuous Multiclass Labeling Approaches And Algorithms. Univ. of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/10460/\par \par  Lellmann, J, Breitenreicher, D and Schn\'f6rr, C (2010). Fast and Exact Primal-Dual Iterations for Variational Problems in Computer Vision. European Conference on Computer Vision (ECCV). Springer Berlin / Heidelberg. 6312 494?505\par \par  Kappes, J H, Schmidt, S and Schn\'f6rr, C (2010). MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation. European Conference on Computer Vision (ECCV). Springer Berlin / Heidelberg. 6313 735?747\par \par  Vlasenko, A and Schn\'f6rr, C (2010). Physically Consistent and Efficient Variational Denoising of Image Fluid Flow Estimates. IEEE Trans. Image Proc. 19 586-595\par \par  Heitz, D, M\'e9min, E and Schn\'f6rr, C (2010). Variational fluid flow measurements from image sequences: synopsis and perspectives. Exp. Fluids. 48 369-393\par \par  Nicola, A, Petra, S, Popa, C and Schn\'f6rr, C (2009). On A General Extending And Constraining Procedure For Linear Iterative Methods. IWR, University of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/9761\par \par  Lauer, F and Schn\'f6rr, C (2009). Spectral Clustering of Linear Subspaces for Motion Segmentation. Proc. IEEE Int. Conf. Computer Vision (ICCV'09). Kyoto, Japan\par \par  Petra, S and Schn\'f6rr, C (2009). TomoPIV meets Compressed Sensing. Pure Math. Appl. 20 49 ? 76. http://www.mat.unisi.it/newsito/puma/public_html/contents.php\par \par  Petra, S and Schn\'f6rr, C (2009). Tomopiv Meets Compressed Sensing. IWR, University of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/9760\par \par  Vlasenko, A and Schn\'f6rr, C (2009). Variational Approaches for Model-Based PIV and Visual Fluid Analysis. Imaging Measurement Methods for Flow Analysis. Springer. 106 247-256\par \par  Petra, S, Popa, C and Schn\'f6rr, C (2008). Enhancing Sparsity by Constraining Strategies: Constrained SIRT versus Spectral Projected Gradient Methods. Proc. 7th Workshop on Modelling of Environmental and Life Sciences Problems (WMM 08). Bucharest, Romania\par \par  Petra, S, Popa, C and Schn\'f6rr, C (2008). Enhancing Sparsity by Constraining Strategies: Constrained SIRT versus Spectral Projected Gradient Methods. Proc. 7th Workshop on Modelling of Environmental and Life Sciences Problems (WMM 08). Ed Acad Romane, Bucuresti, Constanta, Romania\par \par  Kappes, J H and Schn\'f6rr, C (2008). MAP-Inference for Highly-Connected Graphs with DC-Programming. Pattern Recognition ? 30th DAGM Symposium. Springer Verlag. 5096 1?10\par \par  Munder, S, Schn\'f6rr, C and Gavrila, D M (2008). Pedestrian Detection and Tracking Using a Mixture of View-Based Shape-Texture Models. IEEE Trans. Intell. Transp. Systems. 9 333-343\par \par  Vlasenko, A and Schn\'f6rr, C (2008). Physically Consistent Variational Denoising of Image Fluid Flow Estimates. Pattern Recognition ? 30th DAGM Symposium. Springer Verlag. 5096 406?415\par \par  Petra, S, Schr\'f6der, A, Wieneke, B and Schn\'f6rr, C (2008). On Sparsity Maximization in Tomographic Particle Image Reconstruction. Pattern Recognition ? 30th DAGM Symposium. Springer Verlag. 5096 294?303\par \par  Schellewald, C, Roth, S and Schn\'f6rr, C (2007). Evaluation of a convex relaxation to a quadratic assignment matching approach for relational object views. Image Vision Comp. 25 1301?1314\par \par  Karim, R, Bergtholdt, M, Kappes, J H and Schn\'f6rr, C (2007). Greedy-Based Design of Sparse Two-Stage SVMs for Fast Classification. Pattern Recognition ? 29th DAGM Symposium. Springer. 4713 395-404\par \par  Welk, M, Weickert, J, Becker, F, Schn\'f6rr, C, Feddern, C and Burgeth, B (2007). Median and related local filters for tensor-valued images. Signal Processing. 87 291-308\par \par  Ruhnau, P and Schn\'f6rr, C (2007). Optical Stokes Flow Estimation: An Imaging-Based Control Approach. Exp. in Fluids. 42 61?78\par \par  Schn\'f6rr,  (2007). Signal and Image Approximation with Level-Set Constraints. Computing. 81 137-160\par \par  Yuan, J, Schn\'f6rr, C and Steidl, G (2007). Simultaneous Optical Flow Estimation and Decomposition. SIAM J. Scientific Computing. 29 2283-2304\par \par  Schmidt, S, Kappes, J H, Bergtholdt, M, Pekar, V, Dries, S, Bystrov, D and Schn\'f6rr, C (2007). Spine Detection and Labeling Using a Parts-Based Graphical Model. Proc. 20th International Conference on Information Processing in Medical Imaging (IPMI 2007). Springer. 4584 122-133\par \par  Petra, S, Schn\'f6rr, C, Schr\'f6der, A and Wieneke, B (2007). Tomographic Image Reconstruction in Experimental Fluid Dynamics: Synopsis and Problems. Proc. 6th Workshop on Modelling of Environmental and Life Sciences Problems (WMM 07). Ed Acad Romane, Bucuresti, Constanta, Romania\par \par  Ruhnau, P, Stahl, A and Schn\'f6rr, C (2007). Variational Estimation of Experimental Fluid Flows with Physics-Based Spatio-Temporal Regularization. Measurement Science and Technology. 18 755-763\par \par  Schn\'f6rr, C, Sch\'fcle, T and Weber, S (2007). Variational Reconstruction with DC-Programming. Advances in Discrete Tomography and Its Applications. Birkh\'e4user, Boston\par \par  Heiler, M and Schn\'f6rr, C (2006). Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming. J. Mach. Learning Res. 7 1385?1407. http://www.cvgpr.uni-mannheim.de/Publications\par \par  Ruhnau, P, Stahl, A and Schn\'f6rr, C (2006). On-Line Variational Estimation of Dynamical Fluid Flows with Physics-Based Spatio-Temporal Regularization. Proc. DAGM 2006. Springer. 375-388 375-388\par \par  Sch\'fcle, T, Weber, S and Schn\'f6rr, C (2005). Adaptive Reconstruction of Discrete-Valued Objects from few Projections. Electr. Notes in Discr. Math. 20 365-384\par \par  Weber, S, Schn\'f6rr, C, Sch\'fcle, T and Hornegger, J (2005). Binary Tomography by Iterating Linear Programs. Geometric Properties from Incomplete Data. Springer\par \par  Neumann, J, Schn\'f6rr, C and Steidl, G (2005). Combined SVM-based Feature Selection and Classification. Machine Learning. 61 129-150\par \par  Yuan, J, Ruhnau, P, M\'e9min, E and Schn\'f6rr, C (2005). Discrete Orthogonal Decomposition and Variational Fluid Flow Estimation. Scale-Space 2005. Springer. 3459 267?278\par \par  Sch\'fcle, T, Schn\'f6rr, C, Weber, S and Hornegger, J (2005). Discrete Tomography By Convex-Concave Regularization and D.C. Programming. Discr. Appl. Math. 151 229-243\par \par  Kohlberger, T, Schn\'f6rr, C, Bruhn, A and Weickert, J (2005). Domain decomposition for variational optical flow computation. IEEE Trans. Image Proc. 14 1125-1137\par \par  Neumann, J, Schn\'f6rr, C and Steidl, G (2005). Efficient Wavelet Adaption for Hybrid Wavelet-Large Margin Classifiers. Pattern Recognition. 38 1815-1830\par \par  Heiler, M and Schn\'f6rr, C (2005). Learning Sparse Image Codes by Convex Programming. Proc. Tenth IEEE Int. Conf. Computer Vision (ICCV'05). Beijing, China. 1667-1674\par \par  Heiler, M and Schn\'f6rr, C (2005). Natural Image Statistics for Natural Image Segmentation. Int. J. Comp. Vision. 63 5?19\par \par  Weber, S, Sch\'fcle, T and Schn\'f6rr, C (2005). Prior Learning and Convex-Concave Regularization of Binary Tomography. Electr. Notes in Discr. Math. 20 313-327\par \par  Schellewald, C and Schn\'f6rr, C (2005). Probabilistic Subgraph Matching Based on Convex Relaxation. Proc. Int. Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'05). Springer. 3757 171-186\par \par  Heiler, M and Schn\'f6rr, C (2005). Reverse-Convex Programming for Sparse Image Codes. Proc. Int. Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'05). Springer. 3757 600-616\par \par  Heiler, M, Keuchel, J and Schn\'f6rr, C (2005). Semidefinite Clustering for Image Segmentation with A-priori Knowledge. Pattern Recognition, Proc. 27th DAGM Symposium. Springer. 3663 309?317\par \par  Ruhnau, P, G\'fctter, C, Putze, T and Schn\'f6rr, C (2005). A variational approach for particle tracking velocimetry. Meas. Science and Techn. 16 1449-1458\par \par  (2005). Variational, Geometric and Level Sets in Computer Vision (VLSM'05). lncs. Springer, Beijing, China. 3752\par \par  Ruhnau, P, Kohlberger, T, Nobach, H and Schn\'f6rr, C (2005). Variational Optical Flow Estimation for Particle Image Velocimetry. Experiments in Fluids. 38 21?32\par \par  Giebel, J, Gavrila, D M and Schn\'f6rr, C (2004). A Bayesian Framework for Multi-cue 3D Object Tracking. Computer Vision ? ECCV 2004. Springer. 3024 241-252\par \par  Weber, S, Sch\'fcle, T, Hornegger, J and Schn\'f6rr, C (2004). Binary Tomography by Iterating Linear Programs from Noisy Projections. Combinatorial Image Analysis, Proc. Int. Workshop on Combinatorial Image Analysis (IWCIA'04). Springer Verlag. 3322 38?51\par \par  Yuan, J, Schn\'f6rr, C, Kohlberger, T and Ruhnau, P (2004). Convex Set-Based Estimation of Image Flows. ICPR 2004 ? 17th Int. Conf. on Pattern Recognition. IEEE, Cambridge, UK. 1 124-127\par \par  Keuchel, J, Heiler, M and Schn\'f6rr, C (2004). Hierarchical Image Segmentation based on Semidefinite Programming. Pattern Recognition, Proc. 26th DAGM Symposium. Springer. 3175 120-128\par \par  Weber, S, Sch\'fcle, T, Schn\'f6rr, C and Hornegger, J (2004). A Linear Programming Approach to Limited Angle 3D Reconstruction from DSA Projections. Methods of Information in Medicine. 43 320?326\par \par  Kohlberger, T, Schn\'f6rr, C, Bruhn, A and Weickert, J (2004). Parallel Variational Motion Estimation by Domain Decomposition and Cluster Computing. Computer Vision ? ECCV 2004. Springer. 3024 205-216\par \par  Neumann, J, Schn\'f6rr, C and Steidl, G (2004). SVM-based Feature Selection by Direct Objective Minimisation. Pattern Recognition, Proc. 26th DAGM Symposium. Springer. 3175 212-219\par \par  Ruhnau, P, Kohlberger, T, Nobach, H and Schn\'f6rr, C (2004). Variational Optical Flow Estimation for Particle Image Velocimetry. Proc. Lasermethoden in der Str\'f6mungsme\'dftechnik. Deutsche Gesellschaft f\'fcr Laser-Anemometrie GALA e.V., Karlsruhe\par \par  Keuchel, J, Schn\'f6rr, C, Schellewald, C and Cremers, D (2003). Binary Partitioning, Perceptual Grouping, and Restoration with Semidefinite Programming. 25 1364?1379\par \par  Sch\'fcle, T, Schn\'f6rr, C, Weber, S and Hornegger, J (2003). Discrete Tomography By Convex-Concave Regularization And D.c. Programming. Dept. Math. and Comp. Science, University of Mannheim, Germany\par \par  Kohlberger, T, Schn\'f6rr, C, Bruhn, A and Weickert, J (2003). Domain Decomposition for Parallel Variational Optical Flow Computation. Pattern Recognition, Proc. 25th DAGM Symposium. Springer. 2781 196?203\par \par  Kohlberger, T, Schn\'f6rr, C, Bruhn, A and Weickert, J (2003). Domain Decomposition For Variational Optical Flow Computation. Dept. Math. and Comp. Science, University of Mannheim, Germany\par \par  Neumann, J, Schn\'f6rr, C and Steidl, G (2003). Effectively Finding The Optimal Wavelet For Hybrid Wavelet - Large Margin Signal Classification. Dept. Math. and Comp. Science, University of Mannheim, Germany\par \par  Neumann, J, Schn\'f6rr, C and Steidl, G (2003). Feasible Adaption Criteria for Hybrid Wavelet ? Large Margin Classifiers. Proc. Computer Analysis of Images and Patterns (CAIP'03). Springer. 2756 588?595\par \par  Weber, S, Sch\'fcle, T, Schn\'f6rr, C and Hornegger, J (2003). A Linear Programming Approach to Limited Angle 3D Reconstruction from DSA Projections. Bildverarbeitung f\'fcr die Medizin 2003. Springer Verlag. 41?45\par \par  Weber, S, Schn\'f6rr, C and Hornegger, J (2003). A Linear Programming Relaxation for Binary Tomography with Smoothness Priors. Proc. Int. Workshop on Combinatorial Image Analysis (IWCIA'03). Palermo, Italy\par \par  Heiler, M and Schn\'f6rr, C (2003). Natural Statistics for Natural Image Segmentation. Proc. IEEE Int. Conf. Computer Vision (ICCV 2003). Nice, France. 1259-1266\par \par  Schellewald, C and Schn\'f6rr, C (2003). Subgraph Matching with Semidefinite Programming. Proc. Int. Workshop on Combinatorial Image Analysis (IWCIA'03). Palermo, Italy\par \par  Kohlberger, T, M\'e9min, E and Schn\'f6rr, C (2003). Variational Dense Motion Estimation Using the Helmholtz Decomposition. Scale Space Methods in Computer Vision. Springer. 2695 432?448\par \par  Schellewald, C, Roth, S and Schn\'f6rr, C (2002). Performance Evaluation Of A Convex Relaxation Approach To The Quadratic Assignment Of Relational Object Views. Dept. Math. and Comp. Science, University of Mannheim, Germany\par \par  Keuchel, J, Schn\'f6rr, C, Schellewald, C and Cremers, D (2002). Unsupervised Image Partitioning with Semidefinite Programming. Pattern Recognition, Proc. 24th DAGM Symposium. Springer, Z\'fcrich, Switzerland. 2449 141?149\par \par  Wiehler, K, Heers, J, Schn\'f6rr, C, Stiehl, H ?S and Grigat, R ?R (2001). A 1D analog VLSI implementation for non-linear real-time signal preprocessing. Real?Time Imaging. 7 127?142\par \par  Schellewald, C, Roth, S and Schn\'f6rr, C (2001). Application Of Convex Optimization Techniques To The Relational Matching Of Object Views. Dept. Math. and Comp. Science, University of Mannheim, Germany\par \par  Keuchel, J, Schellewald, C, Cremers, D and Schn\'f6rr, C (2001). Convex Relaxations for Binary Image Partitioning and Perceptual Grouping. Mustererkennung 2001. Springer, Munich, Germany. 2191 353?360\par \par  Heiler, M, Cremers, D and Schn\'f6rr, C (2001). Efficient Feature Subset Selection For Support Vector Machines. Dept. Math. and Comp. Science, University of Mannheim, Germany\par \par  Schellewald, C, Roth, S and Schn\'f6rr, C (2001). Evaluation of Convex Optimization Techniques for the Weighted Graph?Matching Problem in Computer Vision. Mustererkennung 2001. Springer, Munich, Germany. 2191 361?368\par \par  Weickert, J, Heers, J, Schn\'f6rr, C, Zuiderveld, K ?J, Scherzer, O and Stiehl, H ?S (2001). Fast parallel algorithms for a broad class of nonlinear variational diffusion approaches. Real?Time Imaging. 7 31?45\par \par  Heers, J, Schn\'f6rr, C and Stiehl, H S (2001). Globally?Convergent Iterative Numerical Schemes for Non?Linear Variational Image Smoothing and Segmentation on a Multi?Processor Machine. IEEE Trans. Image Proc. 10 852?864\par \par  Schellewald, C, Keuchel, J and Schn\'f6rr, C (2001). Image labeling and grouping by minimizing linear functionals over cones. Proc. Third Int. Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'01). Springer, INRIA, Sophia Antipolis, France. 2134 267?282\par \par  Weickert, J and Schn\'f6rr, C (2001). A Theoretical Framework for Convex Regularizers in PDE?Based Computation of Image Motion. Int. J. Computer Vision. 45 245?264\par \par  Weickert, J and Schn\'f6rr, C (2001). Variational Optic Flow Computation with a Spatio-Temporal Smoothness Constraint. J. Math. Imaging and Vision. 14 245?255\par \par  Wulf, M, Stiehl, H S and Schn\'f6rr, C (2000). On the computational r\'f4le of the primate retina. Proc. 2nd ICSC Symposium on Neural Computation (NC 2000). Berlin, Germany\par \par  (2000). K\'fcnstliche Intelligenz: Special Issue on Medical Computer Vision. 3\par \par  Weickert, J and Schn\'f6rr, C (2000). PDE?Based Preprocessing of Medical Images. K\'fcnstliche Intelligenz. 3 5?10\par \par  Schn\'f6rr,  (2000). Variational Adaptive Smoothing and Segmentation. Computer Vision and Applications: A Guide for Students and Practitioners. Academic Press, San Diego. 459?482\par \par  Schn\'f6rr, C and Weickert, J (2000). Variational Image Motion Computation: Theoretical Framework, Problems and Perspectives. Mustererkennung 2000. Springer, Kiel, Germany\par \par  Heers, J, Schn\'f6rr, C and Stiehl, H S (1999). Investigating A Class Of Iterative Schemes And Their Parallel Implementation For Nonlinear Variational Image Smoothing And Segmentation. Comp. Sci. Dept., AB KOGS, University of Hamburg, Germany\par \par  Wulf, M, Stiehl, H S and Schn\'f6rr, C (1999). A model of spatiotemporal receptive fields in the primate retina. Proc. 1st G\'f6ttingen Conf. German Neurosci. Soc.. II\par \par  Wulf, M, Stiehl, H S and Schn\'f6rr, C (1999). Modeling spatiotemporal receptive fields in the primate retina. Proc. Cognitive Neurosci. Conf. Hanse?Wissenschaftskolleg, Bremen, Germany\par \par  Peckar, W, Schn\'f6rr, C, Rohr, K and Stiehl, H ?S (1999). Parameter-Free Elastic Deformation Approach for 2D and 3D Registration Using Prescribed Displacements. J. Math. Imaging and Vision. 10 143?162\par \par  Weickert, J and Schn\'f6rr, C (1999). R\'e4umlich?zeitliche Berechnung des optischen Flusses mit nichtlinearen flussabh\'e4ngigen Glattheitstermen. Mustererkennung 1999. Springer. 317?324\par \par  Schn\'f6rr,  (1999). Variational Methods for Adaptive Image Smoothing and Segmentation. Handbook on Computer Vision and Applications: Signal Processing and Pattern Recognition. Academic Press, San Diego. 2 451?484\par \par  Heers, J, Schn\'f6rr, C and Stiehl, H S (1998). A class of parallel algorithms for nonlinear variational image segmentation. Proc. Noblesse Workshop on Non?Linear Model Based Image Analysis (NMBIA'98). Glasgow, Scotland\par \par  Wiehler, K, Grigat, R ?R, Heers, J, Schn\'f6rr, C and Stiehl, H S (1998). Dynamic Circular Cellular Networks for Adaptive Smoothing of Multi?Dimensional Signals. Proc. 5th IEEE Int. Workshop on Cellular Neural Networks and their Applications. London\par \par  Heers, J, Schn\'f6rr, C and Stiehl, H ?S (1998). Investigation of Parallel and Globally Convergent Iterative Schemes for Nonlinear Variational Image Smoothing and Segmentation. Proc. IEEE Int. Conf. Image Proc. Chicago\par \par  Peckar, W, Schn\'f6rr, C, Rohr, K, Stiehl, H ?S and Spetzger, U (1998). Linear and Incremental Estimation of Elastic Deformations in Medical Registration Using Prescribed Displacements. Machine Graphics & Vision. 7 807?829\par \par  Peckar, W, Schn\'f6rr, C, Rohr, K and Stiehl, H S (1998). Non-Rigid Image Registration Using a Parameter-Free Elastic Model. 9th British Machine Vision Conference (BMVC`98). Southampton/UK. 134?143\par \par  Heers, J, Schn\'f6rr, C and Stiehl, H ?S (1998). Parallele und global konvergente iterative Minimierung nichtlinearer Variationsans\'e4tze zur adaptiven Gl\'e4ttung und Segmentation von Bildern. Mustererkennung 1998. Springer, Heidelberg\par \par  Wiehler, K, Grigat, R ?R, Heers, J, Schn\'f6rr, C and Stiehl, H ?S (1998). Real?Time Adaptive Smoothing with a 1D Nonlinear Relaxation Network in Analogue VLSI Technology. Mustererkennung 1998. Springer, Heidelberg\par \par  Schn\'f6rr,  (1998). A Study of a Convex Variational Diffusion Approach for Image Segmentation and Feature Extraction. J. of Math. Imag. and Vision. 8 271?292\par \par  Schn\'f6rr,  (1998). Variational approaches to Image Segmentation and Feature Extraction. University of Hamburg, Comp. Sci. Dept., Hamburg, Germany\par \par  Gerloff, S, Hagemann, A, Schn\'f6rr, C, Tieck, S, Stiehl, H S, Dombrowski, R, Dreyer, M and Wiesendanger, R (1997). Semi?Automated Analysis of SXM Images. Proc. 9th Int. Conf. on Scanning Tunneling Microscopy/Spectroscopy and Related Techniques (STM'97). Hamburg, Germany\par \par  Peckar, W, Schn\'f6rr, C, Rohr, K and Stiehl, H S (1997). Two-Step Parameter-Free Elastic Image Registration with Prescribed Point Displacements. Proc. 9th Int. Conf. on Image Analysis and Processing (ICIAP'97). Florence, Italy\par \par  Schn\'f6rr,  (1996). Convex Variational Segmentation of Multi-Channel Images. Proc. 12th Int. Conf. on Analysis and Optimization of Systems: Images, Wavelets and PDE's. Springer-Verlag, Paris. 219\par \par  Schn\'f6rr, C, Stiehl, H - S and Grigat, R - R (1996). On Globally Asymptotically Stable Continuous-Time CNNs for Adaptive Smoothing of Multidimensional Signals. Proc. 4th IEEE Int. Workshop on Cellular Neural Networks and their Applications. Seville, Spain\par \par  Schn\'f6rr,  (1996). Repr\'e4sentation von Bilddaten mit einem konvexen Variationsansatz. Mustererkennung 1996. Springer-Verlag, Berlin, Heidelberg. 21?28\par \par  Schn\'f6rr,  (1996). Representation Of Images By A Convex Variational Diffusion Approach. FB Informatik, Universit\'e4t Hamburg\par \par  Schn\'f6rr, C, Sprengel, R and Neumann, B (1996). A Variational Approach to the Design of Early Vision Algorithms. Computing Suppl. 11 149-165\par \par  Schn\'f6rr, C and Peckar, W (1995). Motion-Based Identification of Deformable Templates. Proc. 6th Int. Conf. on Computer Analysis of Images and Patterns (CAIP '95). Springer Verlag, Prague, Czech Republic. 970 122-129\par \par  Schn\'f6rr,  (1994). Bewegungssegmentation von Bildfolgen durch die Minimierung konvexer nicht-quadratischer Funktionale. Mustererkennung 1994. Technische Universit\'e4t Wien. 5 178?185\par \par  Heikkonen, J, Koikkalainen, P and Schn\'f6rr, C (1994). Building Trajectories via Selforganization from Spatiotemporal Features. 12th Int. Conf. on Pattern Recognition. Jerusalem, Israel\par \par  Sprengel, R, Schn\'f6rr, C and Neumann, B (1994). Detection of Visual Data Transitions in Nonlinear Parameter Space. Mustererkennung 1994. Technische Universit\'e4t Wien. 5 315?323\par \par  Schn\'f6rr, C and Sprengel, R (1994). A Nonlinear Regularization Approach to Early Vision. Biol. Cybernetics. 72 141?149\par \par  Schn\'f6rr,  (1994). Segmentation of Visual Motion by Minimizing Convex Non-Quadratic Functionals. 12th Int. Conf. on Pattern Recognition. Jerusalem, Israel\par \par  Schn\'f6rr,  (1994). Unique Reconstruction of Piecewise Smooth Images by Minimizing Strictly Convex Non-Quadratic Functionals. 4 189?198\par \par  Schn\'f6rr, C, Niemann, H and Kopecz, J (1993). Architekturkonzepte zur Bildauswertung. Grundlagen und Anwendungen der K\'fcnstlichen Intelligenz, 17. Fachtagung f\'fcr K\'fcnstliche Intelligenz. Springer-Verlag, Berlin. 268?274\par \par  Schn\'f6rr,  (1993). On Functionals with Greyvalue-Controlled Smoothness Terms for Determining Optical Flow. pami. 15 1074?1079\par \par  Sprengel, R and Schn\'f6rr, C (1993). Nichtlineare Diffusion zur Integration visueller Daten - Anwendung auf Kernspintomogramme. Mustererkennung 1993, 15. DAGM-Symposium. Springer Verlag. 134?141\par \par  Schn\'f6rr,  (1992). Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization. ijcv. 8 153?165\par \par  Schn\'f6rr, C and Neumann, B (1992). Ein Ansatz zur effizienten und eindeutigen Rekonstruktion st\'fcckweise glatter Funktionen. Mustererkennung 1992, 14. DAGM-Symposium. Springer-Verlag, Dresden. 411?416\par \par  Schn\'f6rr,  (1991). Determining Optical Flow for Irregular Domains by Minimizing Quadratic Functionals of a Certain Class. ijcv. 6 25?38\par \par  Schn\'f6rr,  (1991). Funktionalanalytische Methoden zur Bestimmung von Bewegungsinformation aus TV-Bildfolgen. Fakult\'e4t f\'fcr Informatik, Universit\'e4t Karlsruhe (TH)\par \par  Bister, D, Rohr, K and Schn\'f6rr, C (1990). Automatische Bestimmung der Trajektorien von sich bewegenden Objekten aus einer Grauwertbildfolge. Mustererkennung 1990, 12. DAGM-Symposium. Springer-Verlag, Oberkochen-Aalen. 254 44?51\par \par  Schn\'f6rr,  (1990). Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization. Proc. British Machine Vision Conference. Oxford/UK. 109?114\par \par  Schn\'f6rr,  (1989). Zur Sch\'e4tzung von Geschwindigkeitsvektorfeldern in Bildfolgen mit einer richtungsabh\'e4ngigen Glattheitsforderung. Mustererkennung 1989, 11. DAGM-Symposium. Springer-Verlag, Hamburg. 219 294?301\par \par }