@conference {Zisler2016a,
	title = {Discrete Tomography by Continuous Multilabeling Subject to Projection Constraints},
	booktitle = {Proc. GCPR},
	year = {2016},
	author = {M. Zisler and Petra, S. and Schn{\"o}rr, Cl. and Christoph Schn{\"o}rr}
}
@conference {Berger2016a,
	title = {Joint Recursive Monocular Filtering of Camera Motion and Disparity Map},
	booktitle = {38th German Conference on Pattern Recognition},
	year = {2016},
	publisher = {Springer},
	organization = {Springer},
	address = {Hannover},
	doi = {1606.02092},
	url = {https://arxiv.org/abs/1606.02092},
	author = {Johannes Berger and Christoph Schn{\"o}rr}
}
@conference {Berger2016a,
	title = {Joint Recursive Monocular Filtering of Camera Motion and Disparity Map},
	booktitle = {38th German Conference on Pattern Recognition},
	year = {2016},
	note = {in press},
	author = {Johannes Berger and Christoph Schn{\"o}rr}
}
@article {Kappes2016,
	title = {Multicuts and Perturb \& MAP for Probabilistic Graph Clustering},
	journal = {Journal of Mathematical Imaging and Vision},
	volume = {56},
	number = {2},
	year = {2016},
	month = {jan},
	pages = {221{\textendash}237},
	abstract = {We present a probabilistic graphical model formulation for the graph clustering problem. This enables us to locally represent uncertainty of image partitions by approximate marginal distributions in a mathematically substantiated way, and to rectify local data term cues so as to close contours and to obtain valid partitions. We exploit recent progress on globally optimal MAP inference by integer programming and on perturbation-based approximations of the log-partition function, in order to sample clusterings and to estimate marginal distributions of node-pairs both more accurately and more efficiently than state-of-the-art methods. Our approach works for any graphically represented problem instance. This is demonstrated for image segmentation and social network cluster analysis. Our mathematical ansatz should be relevant also for other combinatorial problems.},
	keywords = {Correlation clustering, graphical models, Multicut, Perturb and MAP},
	issn = {15737683},
	doi = {10.1007/s10851-016-0659-3},
	url = {http://arxiv.org/abs/1601.02088},
	author = {Kappes, Jorg Hendrik and Swoboda, Paul and Savchynskyy, Bogdan and Hazan, Tamir and Christoph Schn{\"o}rr}
}
@article {Zisler2016,
	title = {Non-Binary Discrete Tomography by Continuous Non-Convex Optimization},
	journal = {IEEE Comp. Imaging},
	volume = {2},
	number = {3},
	year = {2016},
	pages = {335-347},
	author = {M. Zisler and Kappes, J.H. and Schn{\"o}rr, Cl. and Petra, S. and Christoph Schn{\"o}rr}
}
@article {Swoboda2016,
	title = {Partial Optimality by Pruning for MAP-Inference with General Graphical Models},
	journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
	volume = {38},
	number = {7},
	year = {2016},
	month = {jul},
	pages = {1370{\textendash}1382},
	publisher = {IEEE Computer Society},
	abstract = {We consider the energy minimization problem for undirected graphical models, also known as MAP-inference problem for Markov random fields which is NP-hard in general. We propose a novel polynomial time algorithm to obtain a part of its optimal non-relaxed integral solution. Our algorithm is initialized with variables taking integral values in the solution of a convex relaxation of the MAP-inference problem and iteratively prunes those, which do not satisfy our criterion for partial optimality. We show that our pruning strategy is in a certain sense theoretically optimal. Also empirically our method outperforms previous approaches in terms of the number of persistently labelled variables. The method is very general, as it is applicable to models with arbitrary factors of an arbitrary order and can employ any solver for the considered relaxed problem. Our method{\textquoteright}s runtime is determined by the runtime of the convex relaxation solver for the MAP-inference problem.},
	keywords = {energy minimization, Local polytope, MAP-inference, Markov random fields, partial optimality, persistency},
	issn = {01628828},
	doi = {10.1109/TPAMI.2015.2484327},
	author = {Swoboda, Paul and Shekhovtsov, Alexander and Kappes, Jorg Hendrik and Christoph Schn{\"o}rr and Savchynskyy, Bogdan}
}
@proceedings {6110,
	title = {Plane Wave Acoustic Superposition for Fast Ultrasound Imaging},
	year = {2016},
	author = {Ecaterina Bodnariuc and Martin F. Schiffner and Stefania Petra and Christoph Schn{\"o}rr}
}
@conference {Biesdorf2015,
	title = {3D Segmentation of Vessels by Incremental Implicit Polynomial Fitting and Convex Optimization},
	booktitle = {Proc.~ISBI},
	year = {2015},
	author = {Biesdorf, A. and W{\"o}rz, S. and von Tengg-Kobligk, H. and Karl Rohr and Christoph Schn{\"o}rr}
}
@conference {Bodnariuc2015,
	title = {Adaptive Dictionary-Based Spatio-temporal Flow Estimation for Echo PIV},
	booktitle = {Proc.~EMMCVPR},
	volume = {8932},
	year = {2015},
	pages = {378--391},
	publisher = {Springer},
	organization = {Springer},
	author = {Ecaterina Bodnariuc and Gurung, A. and Stefania Petra and Christoph Schn{\"o}rr}
}
@conference {5977,
	title = {Adaptive Dictionary-Based Spatio-temporal Flow Estimation for Echo PIV},
	booktitle = {EMMCVPR},
	year = {2015},
	author = {Ecaterina Bodnariuc and Gurung, A. and Stefania Petra and Christoph Schn{\"o}rr}
}
@article {Gianniotis2015,
	title = {Approximate variational inference based on a finite sample of Gaussian latent variables},
	journal = {Patt.~Anal.~Appl.},
	year = {2015},
	doi = {10.1007/s10044-015-0496-9},
	author = {Gianniotis, N. and Christoph Schn{\"o}rr and Molkenthin, C. and Bora, S.S.}
}
@article {kappes_15_comparative,
	title = {A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems},
	journal = {International Journal of Computer Vision},
	year = {2015},
	note = {1},
	pages = {1-30},
	doi = {10.1007/s11263-015-0809-x},
	author = {J{\"o}rg H. Kappes and Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph Schn{\"o}rr and Nowozin, S. and Dhruv Batra and Kim, S. and Bernhard X. Kausler and Thorben Kr{\"o}ger and Lellmann, J. and Komodakis, N. and Savchynskyy, B. and Carsten Rother}
}
@article {Kappes2015,
	title = {A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems},
	journal = {Int.~J.~Comp.~Vision},
	year = {2015},
	note = {in press (preprint: arXiv:1404.0533)},
	author = {J{\"o}rg H. Kappes and Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph Schn{\"o}rr and Nowozin, S. and Dhruv Batra and Kim, S. and Bernhard X. Kausler and Thorben Kr{\"o}ger and Lellmann, J. and Komodakis, N. and Savchynskyy, B. and Carsten Rother}
}
@article {Kappes2015,
	title = {A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems},
	journal = {International Journal of Computer Vision},
	volume = {115},
	number = {2},
	year = {2015},
	pages = {155{\textendash}184},
	abstract = {Szeliski et al. published an influential study in 2006 on energy minimization methods for Markov random fields. This study provided valuable insights in choosing the best optimization technique for certain classes of problems. While these insights remain generally useful today, the phenomenal success of random field models means that the kinds of inference problems that have to be solved changed significantly. Specifically, the models today often include higher order interactions, flexible connectivity structures, large label-spaces of different cardinalities, or learned energy tables. To reflect these changes, we provide a modernized and enlarged study. We present an empirical comparison of more than 27 state-of-the-art optimization techniques on a corpus of 2453 energy minimization instances from diverse applications in computer vision. To ensure reproducibility, we evaluate all methods in the OpenGM 2 framework and report extensive results regarding runtime and solution quality. Key insights from our study agree with the results of Szeliski et al. for the types of models they studied. However, on new and challenging types of models our findings disagree and suggest that polyhedral methods and integer programming solvers are competitive in terms of runtime and solution quality over a large range of model types.},
	keywords = {Benchmark, Combinatorial optimization, Discrete graphical models},
	issn = {15731405},
	doi = {10.1007/s11263-015-0809-x},
	url = {http://hci.iwr.uni-heidelberg.de/opengm2/},
	author = {Kappes, J{\"o}rg H and Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph Schn{\"o}rr and Nowozin, Sebastian and Dhruv Batra and Kim, Sungwoong and Kausler, Bernhard X and Kr{\"o}ger, Thorben and Lellmann, Jan and Komodakis, Nikos and Savchynskyy, Bogdan and Carsten Rother}
}
@article {Kappes2015a,
	title = {A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems},
	journal = {International Journal of Computer Vision},
	volume = {115},
	number = {2},
	year = {2015},
	pages = {155{\textendash}184},
	abstract = {Szeliski et al. published an influential study in 2006 on energy minimization methods for Markov random fields. This study provided valuable insights in choosing the best optimization technique for certain classes of problems. While these insights remain generally useful today, the phenomenal success of random field models means that the kinds of inference problems that have to be solved changed significantly. Specifically, the models today often include higher order interactions, flexible connectivity structures, large label-spaces of different cardinalities, or learned energy tables. To reflect these changes, we provide a modernized and enlarged study. We present an empirical comparison of more than 27 state-of-the-art optimization techniques on a corpus of 2453 energy minimization instances from diverse applications in computer vision. To ensure reproducibility, we evaluate all methods in the OpenGM 2 framework and report extensive results regarding runtime and solution quality. Key insights from our study agree with the results of Szeliski et al. for the types of models they studied. However, on new and challenging types of models our findings disagree and suggest that polyhedral methods and integer programming solvers are competitive in terms of runtime and solution quality over a large range of model types.},
	keywords = {Benchmark, Combinatorial optimization, Discrete graphical models},
	isbn = {25164671.25},
	issn = {15731405},
	doi = {10.1007/s11263-015-0809-x},
	author = {Kappes, J{\"o}rg H and Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph Schn{\"o}rr and Nowozin, Sebastian and Dhruv Batra and Kim, Sungwoong and Kausler, Bernhard X and Kr{\"o}ger, Thorben and Lellmann, Jan and Komodakis, Nikos and Savchynskyy, Bogdan and Carsten Rother}
}
@article {Kappes2015b,
	title = {A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems},
	journal = {International Journal of Computer Vision},
	volume = {115},
	number = {2},
	year = {2015},
	pages = {155{\textendash}184},
	abstract = {Szeliski et al. published an influential study in 2006 on energy minimization methods for Markov random fields. This study provided valuable insights in choosing the best optimization technique for certain classes of problems. While these insights remain generally useful today, the phenomenal success of random field models means that the kinds of inference problems that have to be solved changed significantly. Specifically, the models today often include higher order interactions, flexible connectivity structures, large label-spaces of different cardinalities, or learned energy tables. To reflect these changes, we provide a modernized and enlarged study. We present an empirical comparison of more than 27 state-of-the-art optimization techniques on a corpus of 2453 energy minimization instances from diverse applications in computer vision. To ensure reproducibility, we evaluate all methods in the OpenGM 2 framework and report extensive results regarding runtime and solution quality. Key insights from our study agree with the results of Szeliski et al. for the types of models they studied. However, on new and challenging types of models our findings disagree and suggest that polyhedral methods and integer programming solvers are competitive in terms of runtime and solution quality over a large range of model types.},
	keywords = {Benchmark, Combinatorial optimization, Discrete graphical models},
	issn = {15731405},
	doi = {10.1007/s11263-015-0809-x},
	author = {Kappes, J{\"o}rg H and Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph Schn{\"o}rr and Nowozin, Sebastian and Dhruv Batra and Kim, Sungwoong and Kausler, Bernhard X and Kr{\"o}ger, Thorben and Lellmann, Jan and Komodakis, Nikos and Savchynskyy, Bogdan and Carsten Rother}
}
@article {Rathke2015,
	title = {A Computational Approach to Log-Concave Density Estimation},
	journal = {An. St. Univ. Ovidius Constanta},
	volume = {23},
	number = {3},
	year = {2015},
	pages = {151-166},
	author = {Rathke, F. and Christoph Schn{\"o}rr}
}
@article {rathke2015b,
	title = {A Computational Approach to Log-Concave Density Estimation},
	journal = {An. St. Univ. Ovidius Constanta},
	volume = {23},
	year = {2015},
	pages = {151-166},
	author = {Rathke, Fabian and Christoph Schn{\"o}rr}
}
@conference {Silvestri2015,
	title = {A Convex Relaxation Approach to the Affine Subspace Clustering Problem},
	booktitle = {Proc.~GCPR},
	year = {2015},
	author = {Silvestri, F. and Reinelt, G. and Christoph Schn{\"o}rr}
}
@conference {Neufeld-et-al-2015a,
	title = {Estimating Vehicle Ego-Motion and Piecewise Planar Scene Structure from Optical Flow in a Continuous Framework},
	booktitle = {37th German Conference on Pattern Recognition},
	year = {2015},
	note = {in press},
	author = {Neufeld, Andreas and Johannes Berger and Florian Becker and Lenzen, Frank and Christoph Schn{\"o}rr}
}
@article {Schmitzer2015,
	title = {Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein Modes},
	journal = {J.~Math.~Imag.~Vision},
	volume = {52},
	number = {3},
	year = {2015},
	pages = {436--458},
	url = {http://link.springer.com/article/10.1007/s10851-014-0546-8},
	author = {Bernhard Schmitzer and Christoph Schn{\"o}rr}
}
@conference {Kappes2015a,
	title = {Probabilistic Correlation Clustering and Image Partitioning Using Perturbed Multicuts},
	booktitle = {Proc.~SSVM},
	year = {2015},
	publisher = {Springer},
	organization = {Springer},
	author = {J{\"o}rg H. Kappes and Swoboda, P. and Savchynskyy, B. and Hazan, T. and Christoph Schn{\"o}rr}
}
@conference {Kappes2015c,
	title = {Probabilistic correlation clustering and image partitioning using perturbed Multicuts},
	booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
	volume = {9087},
	year = {2015},
	pages = {231{\textendash}242},
	abstract = {We exploit recent progress on globally optimal MAP inference by integer programming and perturbation-based approximations of the log-partition function. This enables to locally represent uncertainty of image partitions by approximate marginal distributions in a mathematically substantiated way, and to rectify local data term cues so as to close contours and to obtain valid partitions. Our approach works for any graphically represented problem instance of correlation clustering, which is demonstrated by an additional social network example.},
	keywords = {Correlation clustering, Multicut, Perturb and MAP},
	isbn = {9783319184609},
	issn = {16113349},
	doi = {10.1007/978-3-319-18461-6_19},
	author = {Kappes, Jorg Hendrik and Swoboda, Paul and Savchynskyy, Bogdan and Hazan, Tamir and Christoph Schn{\"o}rr}
}
@conference {Berger-et-al-2015a,
	title = {Second Order Minimum Energy Filtering on SE(3) with Nonlinear Measurement Equations},
	booktitle = {Scale Space and Variational Methods in Computer Vision (SSVM 2015)},
	year = {2015},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	abstract = {Accurate camera motion estimation is a fundamental build- ing block for many Computer Vision algorithms. For improved robustness, temporal consistency of translational and rotational camera velocity is often assumed by propagating motion information forward using stochastic filters. Classical stochastic filters, however, use linear approximations for the non-linear observer model and for the non-linear structure of the underlying Lie Group SE(3) and have to approximate the unknown posteriori distribution. In this paper we employ a non-linear measurement model for the camera motion estimation problem that incorporates multiple observation equations. We solve the underlying filtering problem using a novel Minimum Energy Filter on SE(3) and give explicit expressions for the optimal state variables. Experiments on the challenging KITTI benchmark show that, although a simple motion model is only employed, our approach improves rotational velocity esti- mation and otherwise is on par with the state-of-the-art.},
	doi = {10.1007/978-3-319-18461-6_32},
	url = {http://dx.doi.org/10.1007/978-3-319-18461-6_32},
	author = {Johannes Berger and Andreas Neufeld and Florian Becker and Frank Lenzen and Christoph Schn{\"o}rr}
}
@conference {Berger-et-al-2015a,
	title = {Second Order Minimum Energy Filtering on SE(3) with Nonlinear Measurement Equations},
	booktitle = {Scale Space and Variational Methods in Computer Vision (SSVM 2015)},
	year = {2015},
	author = {Johannes Berger and Neufeld, Andreas and Florian Becker and Lenzen, Frank and Christoph Schn{\"o}rr}
}
@booklet {Berger-et-al-2015b,
	title = {Second-Order Recursive Filtering on the Rigid-Motion Lie Group SE(3) Based on Nonlinear Observations},
	year = {2015},
	abstract = {Camera motion estimation from observed scene features is an important task in image processing to increase the accuracy of many methods, e.g. optical flow and structure-from-motion. Due to the curved geometry of the state space SE(3) and the non-linear relation to the observed optical flow, many recent filtering approaches use a first-order approximation and assume a Gaussian a posteriori distribution or restrict the state to Euclidean geometry. The physical model is usually also limited to uniform motions. 
We propose a second-order minimum energy filter with a generalized kinematic model that copes with the full geometry of SE(3) as well as with the nonlinear dependencies between the state space and observations. The derived filter enables reconstructing motions correctly for synthetic and real scenes, e.g. from the KITTI benchmark. Our experiments confirm that the derived minimum energy filter with higher-order state differential equation copes with higher-order kinematics and is also able to minimize model noise. We also show that the proposed filter is superior to state-of-the-art extended Kalman filters on Lie groups in the case of linear observations and that our method reaches the accuracy of modern visual odometry methods.},
	keywords = {Constant Acceleration Model, Lie Group, Minimum Energy Filter, Optimal Control, Recursive Filtering, Visual Odometry},
	url = {http://arxiv.org/abs/1507.06810},
	author = {Johannes Berger and Frank Lenzen and Florian Becker and Andreas Neufeld and Christoph Schn{\"o}rr}
}
@booklet {Berger-et-al-2015b,
	title = {Second-Order Recursive Filtering on the Rigid-Motion Lie Group SE(3) Based on Nonlinear Observations},
	year = {2015},
	note = {ArXiv, preprint},
	url = {http://arxiv.org/abs/1507.06810},
	author = {Johannes Berger and Lenzen, Frank and Florian Becker and Neufeld, Andreas and Christoph Schn{\"o}rr}
}
@conference {Kappes2015b,
	title = {TomoGC: Binary Tomography by Constrained Graph Cuts},
	booktitle = {Proc.~GCPR},
	year = {2015},
	author = {J{\"o}rg H. Kappes and Stefania Petra and Christoph Schn{\"o}rr and M. Zisler}
}
@article {Petra2014,
	title = {Average Case Recovery Analysis of Tomographic Compressive Sensing},
	journal = {Linear Algebra and its Applications},
	volume = {441},
	year = {2014},
	note = {Special issue on Sparse Approximate Solution of Linear Systems},
	pages = {168-198},
	author = {Stefania Petra and Christoph Schn{\"o}rr}
}
@article {kappes_14_comparative,
	title = {A Comparative Study of Modern Inference Techniques for Structured
Discrete Energy Minimization Problems},
	journal = {CoRR},
	year = {2014},
	note = {1},
	url = {http://arxiv.org/abs/1404.0533},
	author = {J{\"o}rg H. Kappes and Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph Schn{\"o}rr and Nowozin, S. and Dhruv Batra and Kim, S. and Bernhard X. Kausler and Thorben Kr{\"o}ger and Lellmann, J. and Komodakis, N. and Savchynskyy, B. and Carsten Rother}
}
@article {kappes-1014-bench-arxiv,
	title = {A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems},
	journal = {CoRR},
	volume = {abs/1404.0533},
	year = {2014},
	url = {http://hci.iwr.uni-heidelberg.de/opengm2/},
	author = {J{\"o}rg H. Kappes and Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph Schn{\"o}rr and Nowozin, Sebastian and Dhruv Batra and Kim, Sungwoong and Bernhard X. Kausler and Thorben Kr{\"o}ger and Lellmann, Jan and Komodakis, Nikos and Savchynskyy, Bogdan and Carsten Rother}
}
@conference {Denitiu2014,
	title = {An Entropic Perturbation Approach to TV-Minimization for Limited-Data Tomography},
	booktitle = {Discrete Geometry for Computer Imagery (DGCI) 2014},
	year = {2014},
	pages = {262--274},
	publisher = {Springer},
	organization = {Springer},
	author = {Andreea Denitiu and Stefania Petra and Schn{\"o}rr, Claudius and Christoph Schn{\"o}rr},
	editor = {Elena Barcucci and Frosini, Andrea and Eds Rinaldi, Simone}
}
@conference {Denitiu2014,
	title = {An Entropic Perturbation Approach to TV-Minimization for Limited-Data Tomography},
	booktitle = {Discrete Geometry for Computer Imagery (DGCI) 2014},
	series = {LNCS},
	year = {2014},
	pages = {262{\textendash}274},
	publisher = {Springer},
	organization = {Springer},
	author = {Andreea Denitiu and Petra, Stefania and Schn{\"o}rr, Claudius and Christoph Schn{\"o}rr},
	editor = {Elena Barcucci and Frosini,Andrea and Eds Rinaldi,Simone}
}
@booklet {SchmitzerSchnoerr-WassersteinModes2014,
	title = {Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein Modes},
	year = {2014},
	note = {preprint},
	author = {Bernhard Schmitzer and Christoph Schn{\"o}rr}
}
@booklet {SchmitzerSchnoerr-WassersteinModes2014,
	title = {Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein Modes},
	year = {2014},
	note = {preprint},
	author = {Bernhard Schmitzer and Christoph Schn{\"o}rr}
}
@conference {kappes_14_map,
	title = {MAP-Inference on Large Scale Higher-Order Discrete Graphical Models by Fusion Moves},
	booktitle = {Computer Vision - {ECCV} 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part {II}},
	year = {2014},
	doi = {10.1007/978-3-319-16181-5_37},
	url = {http://dx.doi.org/10.1007/978-3-319-16181-5_37},
	author = {J{\"o}rg H. Kappes and Thorsten Beier and Christoph Schn{\"o}rr}
}
@conference {Kappes-2014,
	title = {MAP-Inference on Large Scale Higher-Order Discrete Graphical Models by Fusion Moves},
	booktitle = {International Workshop on Graphical Models in Computer Vision},
	year = {2014},
	author = {Kappes, Jorg Hendrik and Thorsten Beier and Christoph Schn{\"o}rr}
}
@incollection {Becker2014,
	title = {Optical Flow},
	year = {2014},
	note = {in press},
	publisher = {Springer},
	edition = {2nd},
	author = {Florian Becker and Petra, Stefania and Christoph Schn{\"o}rr},
	editor = {Scherzer, O.}
}
@article {swoboda_14_partial,
	title = {Partial Optimality by Pruning for MAP-inference with General GraphicalModels},
	year = {2014},
	pages = {1170-1177},
	doi = {10.1109/CVPR.2014.153},
	author = {Swoboda, P. and Savchynskyy, B. and J{\"o}rg H. Kappes and Christoph Schn{\"o}rr}
}
@conference {Swoboda-2014,
	title = {Partial Optimality by Pruning for MAP-inference with General Graphical Models},
	booktitle = {IEEE Conference on Computer Vision and Pattern Recognition 2014},
	year = {2014},
	author = {Swoboda, Paul and Savchynskyy, Bogdan and J{\"o}rg H. Kappes and Christoph Schn{\"o}rr}
}
@conference {Swoboda-2014,
	title = {Partial Optimality by Pruning for MAP-inference with General Graphical Models},
	booktitle = {IEEE Conference on Computer Vision and Pattern Recognition 2014},
	year = {2014},
	author = {Swoboda, Paul and Savchynskyy, Bogdan and Kappes, J{\"o}rg H. and Christoph Schn{\"o}rr}
}
@article {Denitiu2014a,
	title = {Phase Transitions and Cosparse Tomographic Recovery of Compound Solid Bodies from Few Projections},
	journal = {Fundamenta Informaticae},
	volume = {135},
	year = {2014},
	pages = {73--102},
	author = {Andreea Denitiu and Stefania Petra and Schn{\"o}rr, Cl. and Christoph Schn{\"o}rr}
}
@article {Denitiu2014a,
	title = {Phase Transitions and Cosparse Tomographic Recovery of Compound Solid Bodies from Few Projections},
	journal = {Fundamenta Informaticae},
	volume = {135},
	year = {2014},
	pages = {73{\textendash}102},
	author = {Andreea Denitiu and Petra, S. and Schn{\"o}rr, Cl. and Christoph Schn{\"o}rr}
}
@article {rathke2014,
	title = {Probabilistic Intra-Retinal Layer Segmentation in 3-{D} {OCT} Images Using Global Shape Regularization},
	journal = {Med. Image Anal.},
	volume = {18},
	year = {2014},
	pages = {781{\textendash}794},
	author = {Rathke, Fabian and Schmidt, Stefan and Christoph Schn{\"o}rr}
}
@article {Rathke2014,
	title = {Probabilistic Intra-Retinal Layer Segmentation in 3-D OCT Images Using Global Shape Regularization},
	journal = {Medical Image Analysis},
	volume = {18},
	number = {5},
	year = {2014},
	pages = {781-794},
	author = {Rathke, F. and Schmidt, S. and Christoph Schn{\"o}rr}
}
@article {Lenzen-et-al-14,
	title = {Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets},
	journal = {SIAM J.~Imag.~Sci.},
	volume = {7},
	number = {4},
	year = {2014},
	pages = {2139--2174},
	author = {Frank Lenzen and Lellmann, J. and Florian Becker and Christoph Schn{\"o}rr}
}
@article {lenzen_14_solving,
	title = {Solving QVIs for Image Restoration with Adaptive Constraint Sets},
	journal = {SIAM Journal on Imaging Sciences (SIIMS), in press},
	year = {2014},
	note = {1},
	author = {Frank Lenzen and Lellmann, J. and Florian Becker and Christoph Schn{\"o}rr}
}
@conference {petra_13_bsmart,
	title = {B-SMART: Bregman-Based First-Order Algorithms for Non-Negative
Compressed Sensing Problems},
	booktitle = {Proceedings of the 4th International Conference on Scale Space and
Variational Methods in Computer Vision SSVM},
	year = {2013},
	note = {1},
	pages = {110-124},
	doi = {10.1007/978-3-642-38267-3_10},
	author = {Stefania Petra and Christoph Schn{\"o}rr and Florian Becker and Frank Lenzen}
}
@conference {Petra-2013-bsmart,
	title = {B-SMART: Bregman-Based First-Order Algorithms for Non-Negative Compressed Sensing Problems},
	booktitle = {Proceedings of the 4th International Conference on Scale Space and Variational Methods in Computer Vision (SSVM) 2013},
	volume = {7893},
	year = {2013},
	pages = {110-124},
	publisher = {Springer},
	organization = {Springer},
	author = {Stefania Petra and Christoph Schn{\"o}rr and Florian Becker and Frank Lenzen}
}
@article {lenzen_13_class,
	title = {A Class of Quasi-Variational Inequalities for Adaptive Image Denoising
and Decomposition},
	journal = {Computational Optimization and Applications (COAP)},
	volume = {54 (2)},
	year = {2013},
	note = {1},
	pages = {371-398},
	doi = {10.1007/s10589-012-9456-0},
	author = {Frank Lenzen and Florian Becker and Lellmann, J. and Stefania Petra and Christoph Schn{\"o}rr}
}
@article {Lenzen-et-al-13,
	title = {A class of quasi-variational inequalities for adaptive image denoising and decomposition},
	journal = {Computational Optimization and Applications},
	volume = {54},
	number = {2},
	year = {2013},
	pages = {371-398},
	publisher = {Springer Netherlands},
	issn = {0926-6003},
	url = {http://dx.doi.org/10.1007/s10589-012-9456-0},
	author = {Frank Lenzen and Florian Becker and Lellmann, Jan and Stefania Petra and Christoph Schn{\"o}rr}
}
@article {Breitenreicher2012,
	title = {COAL: a generic modelling and prototyping framework for convex optimization problems of variational image analysis},
	journal = {Optimization Methods and Software},
	volume = {28},
	number = {5},
	year = {2013},
	note = {Projectpage: http://sourceforge.net/projects/coalproject/},
	pages = {1081-1094},
	doi = {10.1080/10556788.2012.672571},
	url = {http://www.tandfonline.com/doi/abs/10.1080/10556788.2012.672571},
	author = {Breitenreicher, Dirk and Lellmann, Jan and Christoph Schn{\"o}rr}
}
@conference {kappes_13_comparative,
	title = {A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems},
	booktitle = {CVPR 2013. Proceedings},
	year = {2013},
	note = {1},
	doi = {10.1109/CVPR.2013.175},
	author = {J{\"o}rg H. Kappes and Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph Schn{\"o}rr and Nowozin, S. and Dhruv Batra and Sungwoong, K. and Bernhard X. Kausler and Lellmann, J. and Komodakis, N. and Carsten Rother}
}
@conference {Kappes-2013-benchmark,
	title = {A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problem},
	booktitle = {CVPR},
	year = {2013},
	author = {J{\"o}rg H. Kappes and Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph Schn{\"o}rr and Nowozin, Sebastian and Dhruv Batra and Kim, Sungwoong and Bernhard X. Kausler and Lellmann, Jan and Komodakis, Nikos and Carsten Rother}
}
@booklet {SchmitzerSchnoerr-ShapeMeasures2013,
	title = {Contour Manifolds and Optimal Transport},
	year = {2013},
	note = {preprint},
	author = {Bernhard Schmitzer and Christoph Schn{\"o}rr}
}
@article {SwobodaSchnoerr2013,
	title = {Convex Variational Image Restoration with Histogram Priors},
	journal = {SIAM J.~Imag.~Sci.},
	volume = {6},
	number = {3},
	year = {2013},
	pages = {1719-1735},
	author = {Swoboda, P. and Christoph Schn{\"o}rr}
}
@article {Petra2013,
	title = {Critical Parameter Values and Reconstruction Propertiesof Discrete Tomography: Application to Experimental FluidDynamics},
	journal = {Fundamenta Informaticae},
	volume = {125},
	year = {2013},
	pages = {285--312},
	author = {Stefania Petra and Christoph Schn{\"o}rr and Schr{\"o}der, A.}
}
@article {Lellmann2013,
	title = {Discrete and Continuous Models for Partitioning Problems},
	journal = {Int.~J.~Comp.~Visionz},
	volume = {104},
	number = {3},
	year = {2013},
	pages = {241-269},
	doi = {http://dx.doi.org/10.1007/s11263-013-0621-4},
	author = {Lellmann, J. and Lellmann, B. and Widmann, F. and Christoph Schn{\"o}rr}
}
@conference {savchynskyy_13_global,
	title = {Global MAP-Optimality by Shrinking the Combinatorial Search Area
with Convex Relaxation},
	booktitle = {NIPS. Proceedings},
	year = {2013},
	note = {1},
	pages = {1950-1958},
	author = {Savchynskyy, B. and J{\"o}rg H. Kappes and Swoboda, P. and Christoph Schn{\"o}rr}
}
@conference {SavchynskyyNIPS2013,
	title = {Global MAP-Optimality by Shrinking the Combinatorial Search Area with Convex Relaxation},
	booktitle = {NIPS},
	year = {2013},
	note = {Accepted},
	author = {Savchynskyy, Bogdan and J{\"o}rg H. Kappes and Swoboda, Paul and Christoph Schn{\"o}rr}
}
@conference {SavchynskyyNIPS2013,
	title = {Global MAP-Optimality by Shrinking the Combinatorial Search Area with Convex Relaxation},
	booktitle = {NIPS},
	year = {2013},
	note = {Accepted},
	author = {Savchynskyy, Bogdan and Kappes, Jorg Hendrik and Swoboda, Paul and Christoph Schn{\"o}rr}
}
@conference {SchmitzerSchnoerr-SSVM2013,
	title = {A Hierarchical Approach to Optimal Transport},
	booktitle = {Scale Space and Variational Methods (SSVM 2013)},
	year = {2013},
	pages = {452-464},
	author = {Bernhard Schmitzer and Christoph Schn{\"o}rr}
}
@booklet {Kappes-2013-multicut,
	title = {Higher-order Segmentation via Multicuts},
	howpublished = {ArXiv e-prints},
	year = {2013},
	author = {J{\"o}rg H. Kappes and Speth, Markus and Reinelt, Gerhard and Christoph Schn{\"o}rr}
}
@booklet {Kappes-2013-multicut,
	title = {Higher-order Segmentation via Multicuts},
	howpublished = {ArXiv e-prints},
	year = {2013},
	month = {May},
	author = {Kappes, Jorg Hendrik and Speth, Markus and Reinelt, Gerhard and Christoph Schn{\"o}rr}
}
@article {SchmitzerSchnoerr-JMIV2012,
	title = {Modelling convex shape priors and matching based on the Gromov-Wasserstein distance},
	journal = {Journal of Mathematical Imaging and Vision},
	volume = {46},
	number = {1},
	year = {2013},
	pages = {143-159},
	author = {Bernhard Schmitzer and Christoph Schn{\"o}rr}
}
@article {SchmitzerSchnoerr-JMIV2012,
	title = {Modelling convex shape priors and matching based on the Gromov-Wasserstein distance},
	journal = {Journal of Mathematical Imaging and Vision},
	volume = {46},
	number = {1},
	year = {2013},
	pages = {143-159},
	author = {Bernhard Schmitzer and Christoph Schn{\"o}rr}
}
@conference {SchmitzerSchnoerr-EMMCVPR2013,
	title = {Object Segmentation by Shape Matching with Wasserstein Modes},
	booktitle = {Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2013)},
	year = {2013},
	pages = {123-136},
	author = {Bernhard Schmitzer and Christoph Schn{\"o}rr}
}
@article {lellmann_13_optimality,
	title = {Optimality Bounds for a Variational Relaxation of the Image Partitioning
Problem},
	journal = {Journal of Mathematical Imaging and Vision},
	volume = {47 (3)},
	year = {2013},
	note = {1},
	pages = {239-257},
	doi = {10.1007/s10851-012-0390-7},
	author = {Lellmann, Jan and Frank Lenzen and Christoph Schn{\"o}rr}
}
@conference {swoboda_13_partial,
	title = {Partial Optimality via Iterative Pruning for the Potts Model},
	booktitle = {Proceedings of the 4th International Conference on Scale Space and
Variational Methods in Computer Vision SSVM},
	number = {7893},
	year = {2013},
	note = {1},
	pages = {477-488},
	doi = {10.1007/978-3-642-38267-3_40},
	author = {Swoboda, P. and Savchynskyy, B. and J{\"o}rg H. Kappes and Christoph Schn{\"o}rr}
}
@conference {SwobodaSSVM13,
	title = {Partial Optimality via Iterative Pruning for the Potts Model},
	booktitle = {Scale Space and Variational Methods (SSVM 2013)},
	year = {2013},
	author = {Swoboda, Paul and Savchynskyy, Bogdan and J{\"o}rg H. Kappes and Christoph Schn{\"o}rr}
}
@conference {SwobodaSSVM13,
	title = {Partial Optimality via Iterative Pruning for the Potts Model},
	booktitle = {Scale Space and Variational Methods (SSVM 2013)},
	year = {2013},
	author = {Paul Swoboda and Bogdan Savchynskyy and J{\"o}rg H. Kappes and Christoph Schn{\"o}rr}
}
@conference {swoboda_13_persistency,
	title = {Persistency by Pruning for General Graphical Models},
	booktitle = {submitted to NIPS 2013.},
	year = {2013},
	author = {Swoboda, P. and Savchynskyy, B. and J{\"o}rg H. Kappes and Christoph Schn{\"o}rr}
}
@conference {Kappes-2013,
	title = {Towards Efficient and Exact MAP-Inference for Large Scale Discrete Computer Vision Problems via Combinatorial Optimization},
	booktitle = {CVPR},
	year = {2013},
	author = {J{\"o}rg H. Kappes and Speth, Markus and Reinelt, Gerhard and Christoph Schn{\"o}rr}
}
@conference {Kappes-2013,
	title = {Towards Efficient and Exact MAP-Inference for Large Scale Discrete Computer Vision Problems via Combinatorial Optimization},
	booktitle = {CVPR},
	year = {2013},
	author = {J{\"o}rg H. Kappes and Markus Speth and Gerhard Reinelt and Christoph Schn{\"o}rr}
}
@conference {LNCS80810321,
	title = {Variational Image Segmentation and Cosegmentation with the Wasserstein Distance},
	booktitle = {Energy Minimization Methods in Computer Vision and Pattern Recognition},
	volume = {8081},
	year = {2013},
	pages = {321--334},
	publisher = {Springer},
	organization = {Springer},
	isbn = {978-3-642-40394-1},
	author = {Swoboda, Paul and Christoph Schn{\"o}rr},
	editor = {Heyden, Anders and Kahl, Fredrik and Oskarsson, Magnus and Tai, Xue-Cheng and Olsson, Carl}
}
@conference {LNCS80810321,
	title = {Variational Image Segmentation and Cosegmentation with the Wasserstein Distance},
	booktitle = {Energy Minimization Methods in Computer Vision and Pattern Recognition},
	series = {Lecture Notes in Computer Science},
	volume = {8081},
	year = {2013},
	pages = {321{\textendash}334},
	publisher = {Springer},
	organization = {Springer},
	isbn = {978-3-642-40394-1},
	author = {Paul Swoboda and Christoph Schn{\"o}rr},
	editor = {Anders Heyden and Fredrik Kahl and Carl Olsson and Magnus Oskarsson and Xue-Cheng Tai}
}
@article {becker_13_variational,
	title = {Variational Recursive Joint Estimation of Dense Scene Structure and
Camera Motion from Monocular High Speed Traffic Sequences},
	journal = {International Journal of Computer Vision},
	volume = {105 (3)},
	year = {2013},
	note = {1},
	pages = {269-297},
	doi = {10.1007/s11263-013-0639-7},
	author = {Florian Becker and Frank Lenzen and J{\"o}rg H. Kappes and Christoph Schn{\"o}rr}
}
@article {Becker-et-al-13a,
	title = {Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences},
	journal = {International Journal of Computer Vision},
	volume = {105},
	year = {2013},
	pages = {269--297},
	publisher = {Springer US},
	issn = {0920-5691},
	doi = {10.1007/s11263-013-0639-7},
	url = {http://dx.doi.org/10.1007/s11263-013-0639-7},
	author = {Florian Becker and Frank Lenzen and J{\"o}rg H. Kappes and Christoph Schn{\"o}rr}
}
@article {Becker-et-al-13a,
	title = {Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences},
	journal = {International Journal of Computer Vision},
	volume = {105},
	year = {2013},
	pages = {269{\textendash}297},
	publisher = {Springer US},
	keywords = {Dense depth map, Recursive formulation, Structure from motion, Variational approach},
	issn = {0920-5691},
	doi = {10.1007/s11263-013-0639-7},
	url = {http://dx.doi.org/10.1007/s11263-013-0639-7},
	author = {Florian Becker and Lenzen, Frank and Kappes, J{\"o}rg H. and Christoph Schn{\"o}rr}
}
@conference {kappes_12_bundle,
	title = {A Bundle Approach To Efficient MAP-Inference by Lagrangian Relaxation},
	booktitle = {CVPR. Proceedings},
	year = {2012},
	note = {1},
	pages = {1688-1695},
	doi = {10.1109/CVPR.2012.6247863},
	author = {J{\"o}rg H. Kappes and Savchynskyy, B. and Christoph Schn{\"o}rr}
}
@conference {Kappes2012,
	title = {A Bundle Approach To Efficient MAP-Inference by Lagrangian Relaxation},
	booktitle = {CVPR},
	year = {2012},
	note = {in press},
	author = {J{\"o}rg H. Kappes and Savchynskyy, Bogdan and Christoph Schn{\"o}rr}
}
@article {savchynskyy_12_efficient,
	title = {Efficient MRF Energy Minimization via Adaptive Diminishing Smoothing},
	journal = {UAI. Proceedings},
	year = {2012},
	note = {1},
	pages = {746-755},
	author = {Savchynskyy, B. and Schmidt, S. and J{\"o}rg H. Kappes and Christoph Schn{\"o}rr}
}
@conference {SavchynskyyUAI2012,
	title = {Efficient MRF Energy Minimization via Adaptive Diminishing Smoothing},
	booktitle = {UAI 2012},
	year = {2012},
	note = {in press},
	author = {Savchynskyy, Bogdan and Schmidt, Stefan and J{\"o}rg H. Kappes and Christoph Schn{\"o}rr}
}
@article {Lellmann-et-al-12,
	title = {Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem},
	journal = {Journal of Mathematical Imaging and Vision},
	volume = {47},
	number = {3},
	year = {2012},
	pages = {239-257},
	publisher = {Springer},
	issn = {0924-9907},
	doi = {10.1007/s10851-012-0390-7},
	author = {Lellmann, Jan and Frank Lenzen and Christoph Schn{\"o}rr}
}
@article {Lellmann-et-al-12,
	title = {Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem},
	journal = {Journal of Mathematical Imaging and Vision},
	volume = {47},
	number = {3},
	year = {2012},
	pages = {239-257},
	publisher = {Springer},
	issn = {0924-9907},
	doi = {10.1007/s10851-012-0390-7},
	author = {Lellmann, Jan and Lenzen, Frank and Christoph Schn{\"o}rr}
}
@article {Becker-et-al-11b,
	title = {Variational Adaptive Correlation Method for Flow Estimation},
	journal = {IEEE Transactions on Image Processing},
	volume = {21},
	number = {6},
	year = {2012},
	pages = {3053 -- 3065},
	doi = {10.1109/TIP.2011.2181524},
	author = {Florian Becker and Wieneke, Bernhard and Stefania Petra and Schr{\"o}der, Andreas and Christoph Schn{\"o}rr}
}
@article {Becker-et-al-11b,
	title = {Variational Adaptive Correlation Method for Flow Estimation},
	journal = {IEEE Transactions on Image Processing},
	volume = {21},
	number = {6},
	year = {2012},
	month = {June},
	pages = {3053 {\textendash} 3065},
	doi = {10.1109/TIP.2011.2181524},
	author = {Florian Becker and Wieneke, Bernhard and Petra, Stefania and Schr{\"o}der, Andreas and Christoph Schn{\"o}rr}
}
@conference {Lenzen-et-al-11,
	title = {Variational Image Denoising with Adaptive Constraint Sets},
	booktitle = {LNCS},
	year = {2012},
	pages = {206-217},
	publisher = {Springer},
	organization = {Springer},
	author = {Frank Lenzen and Florian Becker and Lellmann, Jan and Stefania Petra and Christoph Schn{\"o}rr}
}
@conference {Lenzen-et-al-11,
	title = {Variational Image Denoising with Adaptive Constraint Sets},
	booktitle = {Proceedings of the 3rd International Conference on Scale Space and Variational Methods in Computer Vision 2011},
	year = {2012},
	pages = {206-217},
	publisher = {Springer},
	organization = {Springer},
	author = {Lenzen, Frank and Florian Becker and Lellmann, Jan and Petra, Stefania and Christoph Schn{\"o}rr}
}
@conference {SchmitzerSchnoerr-SSVM2011,
	title = {Weakly Convex Coupling Continuous Cuts and Shape Priors},
	booktitle = {Scale Space and Variational Methods (SSVM 2011)},
	year = {2012},
	pages = {423-434},
	author = {Bernhard Schmitzer and Christoph Schn{\"o}rr}
}
@article {Lellmann-Schnoerr-SIIMS-11,
	title = {Continuous Multiclass Labeling Approaches and Algorithms},
	journal = {SIAM J.~Imag.~Sci.},
	volume = {4},
	number = {4},
	year = {2011},
	pages = {1049-1096},
	author = {Lellmann, J. and Christoph Schn{\"o}rr}
}
@conference {schmidt_11_evaluation,
	title = {Evaluation of a First-Order Primal-Dual Algorithm for MRF Energy
Minimization},
	booktitle = {EMMCVPR 2011},
	volume = {6819},
	year = {2011},
	note = {1},
	pages = {89-103},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-642-23094-3_7},
	author = {Schmidt, S. and Savchynskyy, B. and J{\"o}rg H. Kappes and Christoph Schn{\"o}rr}
}
@conference {Schmidt11,
	title = {Evaluation of a First-Order Primal-Dual Algorithm for MRF Energy Minimization},
	booktitle = {EMMCVPR},
	volume = {6819},
	year = {2011},
	pages = {89-103},
	publisher = {Springer},
	organization = {Springer},
	author = {Schmidt, Stefan and Savchynskyy, Bogdan and J{\"o}rg H. Kappes and Christoph Schn{\"o}rr}
}
@conference {Schmidt11,
	title = {Evaluation of a First-Order Primal-Dual Algorithm for MRF Energy Minimization},
	booktitle = {EMMCVPR},
	series = {LNCS},
	volume = {6819},
	year = {2011},
	pages = {89-103},
	publisher = {Springer},
	organization = {Springer},
	author = {Stefan Schmidt and Bogdan Savchynskyy and J{\"o}rg Hendrik Kappes and Christoph Schn{\"o}rr}
}
@article {Nicola-et-al-2011,
	title = {A general extending and constraining procedure for linear iterative methods},
	journal = {Int.~J.~Comp.~Math.},
	year = {2011},
	note = {in press},
	url = {http://dx.doi.org/10.1080/00207160.2011.634002},
	author = {Nicola, A. and Stefania Petra and Popa, C. and Christoph Schn{\"o}rr}
}
@conference {kappes_11_globally,
	title = {Globally Optimal Image Partitioning by Multicuts},
	booktitle = {EMMCVPR},
	year = {2011},
	note = {1},
	pages = {31-44},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-642-23094-3_3},
	author = {J{\"o}rg H. Kappes and Speth, M. and Bj{\"o}rn Andres and Reinelt, G. and Christoph Schn{\"o}rr}
}
@conference {Kappes11,
	title = {Globally Optimal Image Partitioning by Multicuts},
	booktitle = {EMMCVPR},
	year = {2011},
	publisher = {Springer},
	organization = {Springer},
	author = {J{\"o}rg H. Kappes and Speth, Markus and Bj{\"o}rn Andres and Reinelt, Gerhard and Christoph Schn{\"o}rr}
}
@conference {Kappes11,
	title = {Globally Optimal Image Partitioning by Multicuts},
	booktitle = {EMMCVPR},
	year = {2011},
	publisher = {Springer},
	organization = {Springer},
	author = {J{\"o}rg Hendrik Kappes and Markus Speth and Bj{\"o}rn Andres and Gerhard Reinelt and Christoph Schn{\"o}rr}
}
@article {Breitenreicher-Schnoerr-IJCV2011,
	title = {Model-Based Multiple Rigid Object Detection and Registration in Unstructured Range Data},
	journal = {Int.~J.~Comp.~Vision},
	volume = {92},
	year = {2011},
	pages = {32--52},
	doi = {10.1007/s11263-010-0401-3},
	url = {http://www.springerlink.com/content/v266873267180602/},
	author = {Breitenreicher, Dirk and Christoph Schn{\"o}rr}
}
@article {Breitenreicher-Schnoerr-IJCV2011,
	title = {Model-Based Multiple Rigid Object Detection and Registration in Unstructured Range Data},
	journal = {Int. J. Comp. Vision},
	volume = {92},
	year = {2011},
	pages = {32{\textendash}52},
	doi = {10.1007/s11263-010-0401-3},
	url = {http://www.springerlink.com/content/v266873267180602/},
	author = {Breitenreicher, Dirk and Christoph Schn{\"o}rr}
}
@conference {lellmann_11_optimality,
	title = {Optimality Bounds for a Variational Relaxation of the Image Partitioning
Problem},
	booktitle = {Energy Min. Meth. Comp. Vis. Patt. Recogn.},
	year = {2011},
	note = {1},
	pages = {132-146},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1234/12345678},
	author = {Lellmann, J. and Frank Lenzen and Christoph Schn{\"o}rr}
}
@conference {Lellmann2011,
	title = {Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem},
	booktitle = {Energy Min. Meth. Comp. Vis. Patt. Recogn.},
	volume = {6819},
	year = {2011},
	pages = {132--146},
	publisher = {Springer},
	organization = {Springer},
	author = {Lellmann, Jan and Frank Lenzen and Christoph Schn{\"o}rr},
	editor = {Boykov, Y. and Kahl, F. and Schmidt, F. R. and Lempitsky, V. F.}
}
@conference {Lellmann2011,
	title = {Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem},
	booktitle = {Energy Min. Meth. Comp. Vis. Patt. Recogn.},
	series = {LNCS},
	volume = {6819},
	year = {2011},
	pages = {132{\textendash}146},
	publisher = {Springer},
	organization = {Springer},
	author = {Lellmann, Jan and Lenzen, Frank and Christoph Schn{\"o}rr},
	editor = {Boykov, Y. and Kahl, F. and Lempitsky, V. F. and Schmidt, F. R.}
}
@techreport {Lellmann2011b,
	title = {Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem},
	year = {2011},
	month = {Dec},
	institution = {IPA group, Heidelberg University},
	url = {http://arxiv.org/abs/1112.0974},
	author = {Lellmann, Jan and Lenzen, Frank and Christoph Schn{\"o}rr}
}
@conference {rathke_11_order,
	title = {Order Preserving and Shape Prior Constrained Intra-Retinal Layer
Segmentation in Optical Coherence Tomography},
	booktitle = {MICCAI 2011, Proceedings},
	volume = {6893},
	year = {2011},
	note = {1},
	pages = {370-377},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-642-23626-6_46},
	author = {Rathke, F. and Schmidt, S. and Christoph Schn{\"o}rr}
}
@conference {Rathke11,
	title = {Order Preserving and Shape Prior Constrained Intra-Retinal Layer Segmentation in Optical Coherence Tomography},
	booktitle = {MICCAI},
	volume = {6893},
	year = {2011},
	pages = {370--377},
	publisher = {Springer},
	organization = {Springer},
	author = {Rathke, Fabian and Schmidt, Stefan and Christoph Schn{\"o}rr},
	editor = {Fichtinger, Gabor and Martel, Anne L. and Peters, Terry M.}
}
@incollection {rathke2011b,
	title = {Order preserving and shape prior constrained intra-retinal layer segmentation in optical coherence tomography},
	volume = {6893},
	year = {2011},
	pages = {370{\textendash}377},
	publisher = {Springer},
	author = {Rathke, Fabian and Schmidt, Stefan and Christoph Schn{\"o}rr}
}
@conference {Rathke11,
	title = {Order Preserving and Shape Prior Constrained Intra-Retinal Layer Segmentation in Optical Coherence Tomography},
	booktitle = {MICCAI},
	series = {Lecture Notes in Computer Science},
	volume = {6893},
	year = {2011},
	pages = {370{\textendash}377},
	publisher = {Springer},
	organization = {Springer},
	author = {Fabian Rathke and Stefan Schmidt and Christoph Schn{\"o}rr},
	editor = {Fichtinger, Gabor and Martel, Anne L. and Peters, Terry M.}
}
@article {Breitenreicher-Lellmann-Schnoerr2011,
	title = {Sparse Template-Based Variational Image Segmentation},
	journal = {Advances in Adaptive Data Analysis},
	volume = {3},
	year = {2011},
	pages = {149-166},
	author = {Breitenreicher, Dirk and Lellmann, Jan and Christoph Schn{\"o}rr}
}
@article {Breitenreicher-Lellmann-Schnoerr2011,
	title = {Sparse Template-Based Variational Image Segmentation},
	journal = {Advances in Adaptive Data Analysis},
	volume = {3},
	year = {2011},
	pages = {149-166},
	author = {Breitenreicher, Dirk and Lellmann, Jan and Christoph Schn{\"o}rr}
}
@article {savchynskyy_11_study_supplement,
	title = {A Study of Nesterov{\textquoteright}s Scheme for Lagrangian Decomposition and MAP
Labeling},
	journal = {IEEE International Conference on Computer Vision and Pattern Recognition
(CVPR), accepted as oral presentation},
	year = {2011},
	note = {1},
	pages = {1817 - 1823},
	doi = {10.1109/CVPR.2011.5995652},
	author = {Savchynskyy, B. and J{\"o}rg H. Kappes and Schmidt, S. and Christoph Schn{\"o}rr}
}
@conference {Savchynskyy-CVPR2011,
	title = {A Study of Nesterov{\textquoteright}s Scheme for Lagrangian Decomposition and MAP Labeling},
	booktitle = {IEEE International Conference on Computer Vision and Pattern Recognition (CVPR)},
	year = {2011},
	author = {Savchynskyy, B. and J{\"o}rg H. Kappes and Schmidt, S. and Christoph Schn{\"o}rr}
}
@article {becker_11_variational2,
	title = {Variational Adaptive Correlation Method for Flow Estimation},
	journal = {IEEE Transactions on Image Processing},
	volume = {21, 6},
	year = {2011},
	note = {1},
	pages = {3053 - 3065},
	doi = {10.1109/TIP.2011.2181524},
	author = {Florian Becker and Wieneke, B. and Stefania Petra and Schr{\"o}der, A. and Christoph Schn{\"o}rr}
}
@conference {lenzen_11_variational,
	title = {Variational Image Denoising with Adaptive Constraint Sets},
	booktitle = {Proceedings of the 3nd International Conference on Scale Space and
Variational Methods in Computer Vision 2011, in press},
	volume = {6667},
	year = {2011},
	note = {1},
	pages = {206-217},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-642-24785-9_18},
	author = {Frank Lenzen and Florian Becker and Lellmann, J. and Stefania Petra and Christoph Schn{\"o}rr}
}
@conference {becker_11_variational,
	title = {Variational Recursive Joint Estimation of Dense Scene Structure and
Camera Motion from Monocular High Speed Traffic Sequences},
	booktitle = {2011 IEEE International Conference on Computer Vision ICCV},
	year = {2011},
	note = {1},
	pages = {1692-1699},
	doi = {10.1109/ICCV.2011.6126432},
	author = {Florian Becker and Frank Lenzen and J{\"o}rg H. Kappes and Christoph Schn{\"o}rr},
	editor = {Metaxas, D. N. and Quan, L. and Van Gool, L. J. and Sanfeliu, A.}
}
@conference {Becker-et-al-11a,
	title = {Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences},
	booktitle = {2011 IEEE International Conference on Computer Vision (ICCV)},
	year = {2011},
	pages = {1692 -- 1699},
	doi = {10.1109/ICCV.2011.6126432},
	author = {Florian Becker and Frank Lenzen and J{\"o}rg H. Kappes and Christoph Schn{\"o}rr}
}
@conference {Becker-et-al-11a,
	title = {Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences},
	booktitle = {2011 IEEE International Conference on Computer Vision (ICCV)},
	year = {2011},
	pages = {1692 {\textendash} 1699},
	doi = {10.1109/ICCV.2011.6126432},
	author = {Florian Becker and Lenzen, Frank and Kappes, J{\"o}rg H. and Christoph Schn{\"o}rr}
}
@conference {andres_10_empirical,
	title = {An Empirical Comparison of Inference Algorithms for Graphical Models
with Higher Order Factors Using OpenGM},
	booktitle = {Pattern Recognition, Proc.~32th DAGM Symposium},
	number = {6376},
	year = {2010},
	note = {1},
	pages = {353-362},
	doi = {10.1007/978-3-642-15986-2_36},
	author = {Bj{\"o}rn Andres and J{\"o}rg H. Kappes and Ullrich K{\"o}the and Christoph Schn{\"o}rr and Fred A. Hamprecht}
}
@conference {Kappes-DAGM2010,
	title = {An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM},
	booktitle = {Pattern Recognition, Proc.~32th DAGM Symposium},
	year = {2010},
	author = {Bj{\"o}rn Andres and J{\"o}rg H. Kappes and Ullrich K{\"o}the and Christoph Schn{\"o}rr and Fred A. Hamprecht}
}
@conference {Lellmann2010a,
	title = {Fast and Exact Primal-Dual Iterations for Variational Problems in Computer Vision},
	booktitle = {European Conference on Computer Vision (ECCV)},
	volume = {6312},
	year = {2010},
	pages = {494--505},
	publisher = {Springer Berlin / Heidelberg},
	organization = {Springer Berlin / Heidelberg},
	author = {Lellmann, J. and Breitenreicher, D. and Christoph Schn{\"o}rr},
	editor = {Daniilidis, K. and Maragos, P. and Paragios, N.}
}
@conference {kappes_10_mrf,
	title = {MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation},
	booktitle = {European Conference on Computer Vision (ECCV)},
	volume = {6313},
	year = {2010},
	note = {1},
	pages = {735--747},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-642-15558-1_53},
	author = {J{\"o}rg H. Kappes and Schmidt, S. and Christoph Schn{\"o}rr},
	editor = {Daniilidis, K. and Maragos, P. and Paragios, N.}
}
@conference {Kappes-ECCV2010,
	title = {MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation},
	booktitle = {European Conference on Computer Vision (ECCV)},
	volume = {6313},
	year = {2010},
	pages = {735--747},
	publisher = {Springer Berlin / Heidelberg},
	organization = {Springer Berlin / Heidelberg},
	author = {J{\"o}rg H. Kappes and Schmidt, S. and Christoph Schn{\"o}rr},
	editor = {Daniilidis, K. and Maragos, P. and Paragios, N.}
}
@article {lellmann_10_optimality,
	title = {Optimality Bounds for Variational Relaxations of Optimal Partition
Problems},
	year = {2010},
	note = {1},
	author = {Lellmann, J. and Frank Lenzen and Christoph Schn{\"o}rr}
}
@article {Vlasenko-Schnoerr-10,
	title = {Physically Consistent and Efficient Variational Denoising of Image Fluid Flow Estimates},
	journal = {IEEE Trans.~Image Proc.},
	volume = {19},
	number = {3},
	year = {2010},
	pages = {586-595},
	author = {Vlasenko, A. and Christoph Schn{\"o}rr}
}
@article {Breitenreicher-Schnoerr10,
	title = {Robust 3D object registration without explicit correspondence using geometric integration},
	journal = {Machine Vision and Applications},
	volume = {21},
	number = {5},
	year = {2010},
	pages = {601-611},
	doi = {10.1007/s00138-009-0227-6},
	url = {http://www.springerlink.com/content/g20710062l014241/},
	author = {Breitenreicher, Dirk and Christoph Schn{\"o}rr}
}
@article {Breitenreicher-Schnoerr10,
	title = {Robust 3D object registration without explicit correspondence using geometric integration},
	journal = {Machine Vision and Applications},
	volume = {21},
	number = {5},
	year = {2010},
	pages = {601-611},
	doi = {10.1007/s00138-009-0227-6},
	url = {http://www.springerlink.com/content/g20710062l014241/},
	author = {Breitenreicher, Dirk and Christoph Schn{\"o}rr}
}
@article {Bergtholdt-et-al-IJCV-2010,
	title = {A Study of Parts-Based Object Class Detection Using Complete Graphs},
	journal = {Int.~J.~Comp.~Vision},
	volume = {87},
	number = {1-2},
	year = {2010},
	pages = {93-117},
	doi = {10.1007/s11263-009-0209-1},
	url = {http://www.springerlink.com/openurl.asp?genre=article\&id=doi:10.1007/s11263-009-0209-1},
	author = {Bergtholdt, Martin and J{\"o}rg H. Kappes and Schmidt, Stefan and Christoph Schn{\"o}rr}
}
@article {Bergtholdt-et-al-IJCV-2010,
	title = {A Study of Parts-Based Object Class Detection Using Complete Graphs},
	journal = {Int. J. Comp. Vision},
	volume = {87},
	number = {1-2},
	year = {2010},
	pages = {93-117},
	doi = {10.1007/s11263-009-0209-1},
	url = {http://www.springerlink.com/openurl.asp?genre=article\&id=doi:10.1007/s11263-009-0209-1},
	author = {Bergtholdt, Martin and Kappes, J{\"o}rg H. and Schmidt, Stefan and Christoph Schn{\"o}rr}
}
@article {Heitz-et-al-09,
	title = {Variational fluid flow measurements from image sequences: synopsis and perspectives},
	journal = {Exp.~Fluids},
	volume = {48},
	number = {3},
	year = {2010},
	note = {DOI 10.1007/s00348-009-0778-3},
	pages = {369-393},
	author = {Heitz, D. and M{\'e}min, E. and Christoph Schn{\"o}rr}
}
@incollection {Petra-et-al-09a,
	title = {3D Tomography from Few Projections in Experimental Fluid Mechanics},
	volume = {106},
	year = {2009},
	pages = {63-72},
	publisher = {Springer},
	author = {Stefania Petra and Schr{\"o}der, A. and Christoph Schn{\"o}rr},
	editor = {W. Nitsche and C. Dobriloff}
}
@techreport {petra09b,
	title = {Accelerating Constrained SIRT with Applications in Tomographic Particle Image Reconstruction},
	year = {2009},
	institution = {IWR, University of Heidelberg},
	url = {http://www.ub.uni-heidelberg.de/archiv/9477},
	author = {Stefania Petra and Popa, C. and Christoph Schn{\"o}rr}
}
@article {Yuan-et-al-JMIV-09,
	title = {Convex Hodge Decomposition and Regularization of Image Flows},
	journal = {J.~Math.~Imag.~Vision},
	volume = {33},
	number = {2},
	year = {2009},
	pages = {169-177},
	author = {Yuan, Jing and Christoph Schn{\"o}rr and Steidl, Gabriele}
}
@conference {lellmann_09_convex2,
	title = {Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation},
	booktitle = {Scale Space and Variational Methods in Computer Vision (SSVM 2009)},
	volume = {5567},
	year = {2009},
	note = {1},
	pages = {150-162},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-642-02256-2_13},
	author = {Lellmann, J. and J{\"o}rg H. Kappes and Yuan, J. and Florian Becker and Christoph Schn{\"o}rr and M{\'o}rken, K. and Lysaker, M.},
	editor = {Tai, X.-C. and Lie, K.-A.}
}
@conference {Lellmann-et-al-09a,
	title = {Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation},
	booktitle = {Scale Space and Variational Methods in Computer Vision (SSVM 2009)},
	volume = {5567},
	year = {2009},
	pages = {150-162},
	publisher = {Springer},
	organization = {Springer},
	author = {Lellmann, J. and J{\"o}rg H. Kappes and Yuan, J. and Florian Becker and Christoph Schn{\"o}rr},
	editor = {Tai, X.-C. and M{\'o}rken, K. and Lie, K.-A. and Lysaker, M.}
}
@conference {lellmann_09_convex,
	title = {Convex Optimization for Multi-Class Image Labeling with a Novel Family
of Total Variation Based Regularizers},
	booktitle = {Proceedings of the IEEE Conference on Computer Vision (ICCV 09) Kyoto, Japan},
	year = {2009},
	note = {1},
	pages = {646-653},
	doi = {10.1109/ICCV.2009.5459176},
	author = {Lellmann, J. and Florian Becker and Christoph Schn{\"o}rr}
}
@conference {Lellmann2009a,
	title = {Convex Optimization for Multi-Class Image Labeling with a Novel Family of Total Variation Based Regularizers},
	booktitle = {IEEE International Conference on Computer Vision (ICCV)},
	year = {2009},
	pages = {646 -- 653},
	author = {Lellmann, J. and Florian Becker and Christoph Schn{\"o}rr}
}
@techreport {popa09,
	title = {On a general extending and constraining procedure for linear iterative methods},
	year = {2009},
	institution = {IWR, University of Heidelberg},
	url = {http://www.ub.uni-heidelberg.de/archiv/9761},
	author = {Nicola, A. and Stefania Petra and Popa, C. and Christoph Schn{\"o}rr}
}
@conference {Breitenreicher-Schnoerr09a,
	title = {Intrinsic Second-Order Geometric Optimization for Robust Point Set Registration Without Correspondence},
	booktitle = {Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2009)},
	volume = {5681},
	year = {2009},
	pages = {274-287},
	publisher = {Springer},
	organization = {Springer},
	url = {http://www.springerlink.com/content/1470n7577713069q/},
	author = {Breitenreicher, Dirk and Christoph Schn{\"o}rr},
	editor = {Daniel Cremers and Boykov, Y. and Schmidt, F. R. and Blake, A.}
}
@conference {Breitenreicher-Schnoerr09a,
	title = {Intrinsic Second-Order Geometric Optimization for Robust Point Set Registration Without Correspondence},
	booktitle = {Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2009)},
	series = {LNCS},
	volume = {5681},
	year = {2009},
	pages = {274-287},
	publisher = {Springer},
	organization = {Springer},
	url = {http://www.springerlink.com/content/1470n7577713069q/},
	author = {Breitenreicher, Dirk and Christoph Schn{\"o}rr},
	editor = {Daniel Cremers and Boykov, Y. and Blake, A. and Schmidt, F. R.}
}
@conference {lauer_09_spectral,
	title = {Spectral Clustering of Linear Subspaces for Motion Segmentation},
	booktitle = {Proceedings of the IEEE Conference on Computer Vision (ICCV 09) Kyoto, Japan, in press},
	year = {2009},
	note = {1},
	pages = {678-685},
	doi = {10.1109/ICCV.2009.5459173},
	author = {Lauer, F. and Christoph Schn{\"o}rr}
}
@conference {Lauer-Schnoerr-09a,
	title = {Spectral Clustering of Linear Subspaces for Motion Segmentation},
	booktitle = {Proc.~IEEE Int.~Conf.~Computer Vision (ICCV{\textquoteright}09)},
	year = {2009},
	note = {accepted},
	author = {Lauer, F. and Christoph Schn{\"o}rr}
}
@techreport {petra09c,
	title = {TomoPIV meets Compressed Sensing},
	year = {2009},
	institution = {IWR, University of Heidelberg},
	url = {http://www.ub.uni-heidelberg.de/archiv/9760},
	author = {Stefania Petra and Christoph Schn{\"o}rr}
}
@article {Petra-Schnoerr-PUMA-10,
	title = {TomoPIV meets Compressed Sensing},
	journal = {Pure Math.~Appl.},
	volume = {20},
	number = {1-2},
	year = {2009},
	pages = {49 -- 76},
	url = {http://www.mat.unisi.it/newsito/puma/public_html/contents.php},
	author = {Stefania Petra and Christoph Schn{\"o}rr}
}
@conference {Yuan-et-al-09a,
	title = {Total-Variation Based Piecewise Affine Regularization},
	booktitle = {Scale Space and Variational Methods in Computer Vision (SSVM 2009)},
	volume = {5567},
	year = {2009},
	pages = {552-564},
	publisher = {Springer},
	organization = {Springer},
	author = {Yuan, Jing. and Christoph Schn{\"o}rr and Steidl, Gabriele},
	editor = {Tai, X.-C. and M{\'o}rken, K. and Lie, K.-A. and Lysaker, M.}
}
@conference {Yuan-et-al-09a,
	title = {Total-Variation Based Piecewise Affine Regularization},
	booktitle = {Scale Space and Variational Methods in Computer Vision (SSVM 2009)},
	series = {LNCS},
	volume = {5567},
	year = {2009},
	pages = {552-564},
	publisher = {Springer},
	organization = {Springer},
	author = {Yuan, Jing. and Christoph Schn{\"o}rr and Steidl, Gabriele},
	editor = {Tai, X.-C. and M{\'o}rken, K. and Lysaker, M. and Lie, K.-A.}
}
@incollection {Vlasenko-Schnoerr-09a,
	title = {Variational Approaches for Model-Based PIV and Visual Fluid Analysis},
	volume = {106},
	year = {2009},
	pages = {247-256},
	publisher = {Springer},
	author = {Vlasenko, A. and Christoph Schn{\"o}rr},
	editor = {W. Nitsche and C. Dobriloff}
}
@conference {Fundana-Heyden-Gosch-Schnoerr-2008,
	title = {Continuous Graph Cuts for Prior-Based Object Segmentation},
	booktitle = {19th Int.~Conf.~Patt.~Recog.~(ICPR)},
	year = {2008},
	pages = {1--4},
	author = {Fundana, Ketut and Heyden, Anders and Gosch, Christian and Christoph Schn{\"o}rr}
}
@conference {Yuan-et-al-2008b,
	title = {Convex Hodge Decomposition of Image Flows},
	booktitle = {Pattern Recognition -- 30th DAGM Symposium},
	volume = {5096},
	year = {2008},
	pages = {416--425},
	publisher = {Springer Verlag},
	organization = {Springer Verlag},
	author = {Yuan, Jing and Steidl, Gabriele and Christoph Schn{\"o}rr}
}
@techreport {Lellmann2008,
	title = {Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation},
	year = {2008},
	institution = {IWR, University of Heidelberg},
	url = {http://www.ub.uni-heidelberg.de/archiv/8759/},
	author = {Lellmann, J. and J{\"o}rg H. Kappes and Yuan, J. and Florian Becker and Christoph Schn{\"o}rr}
}
@conference {becker_08_decomposition,
	title = {Decomposition of Quadratric Variational Problems},
	booktitle = {Pattern Recognition -- 30th DAGM Symposium},
	volume = {5096},
	year = {2008},
	note = {1},
	pages = {325--334},
	author = {Florian Becker and Christoph Schn{\"o}rr}
}
@conference {Becker-et-al-08a,
	title = {Decomposition of Quadratric Variational Problems},
	booktitle = {Pattern Recognition -- 30th DAGM Symposium},
	volume = {5096},
	year = {2008},
	pages = {325--334},
	publisher = {Springer Verlag},
	organization = {Springer Verlag},
	author = {Florian Becker and Christoph Schn{\"o}rr}
}
@techreport {Petra-et-al08b,
	title = {Extended and Constrained Cimmino-type Algorithms with Applications in Tomographic Image Reconstruction},
	year = {2008},
	institution = {IWR, University of Heidelberg},
	url = {http://www.ub.uni-heidelberg.de/archiv/8798/},
	author = {Stefania Petra and Popa, Constantin and Christoph Schn{\"o}rr}
}
@techreport {Petra-et-al08b,
	title = {Extended and Constrained Cimmino-type Algorithms with Applications in Tomographic Image Reconstruction},
	year = {2008},
	month = {November},
	institution = {IWR, University of Heidelberg},
	type = {Technical Report},
	url = {http://www.ub.uni-heidelberg.de/archiv/8798/},
	author = {Stefania Petra and Constantin Popa and Christoph Schn{\"o}rr}
}
@conference {Kappes-et-al-08,
	title = {MAP-Inference for Highly-Connected Graphs with DC-Programming},
	booktitle = {Pattern Recognition -- 30th DAGM Symposium},
	volume = {5096},
	year = {2008},
	pages = {1--10},
	publisher = {Springer Verlag},
	organization = {Springer Verlag},
	author = {J{\"o}rg H. Kappes and Christoph Schn{\"o}rr}
}
@conference {Vlasenko-et-al-08a,
	title = {Physically Consistent Variational Denoising of Image Fluid Flow Estimates},
	booktitle = {Pattern Recognition -- 30th DAGM Symposium},
	volume = {5096},
	year = {2008},
	pages = {406--415},
	publisher = {Springer Verlag},
	organization = {Springer Verlag},
	author = {Vlasenko, A. and Christoph Schn{\"o}rr}
}
@conference {Petra-et-al-08,
	title = {On Sparsity Maximization in Tomographic Particle Image Reconstruction},
	booktitle = {Pattern Recognition -- 30th DAGM Symposium},
	volume = {5096},
	year = {2008},
	pages = {294--303},
	publisher = {Springer Verlag},
	organization = {Springer Verlag},
	author = {Stefania Petra and Schr{\"o}der, A. and Wieneke, B. and Christoph Schn{\"o}rr}
}
@conference {becker_08_variational,
	title = {A Variational Approach to Adaptive Correlation for Motion Estimation
in Particle Image Velocimetry"},
	booktitle = {Pattern Recognition -- 30th DAGM Symposium},
	volume = {5096},
	year = {2008},
	note = {1},
	pages = {335-344},
	author = {Florian Becker and Wieneke, B. and Yuan, J. and Christoph Schn{\"o}rr}
}
@conference {Becker-et-al-08b,
	title = {A Variational Approach to Adaptive Correlation for Motion Estimation in Particle Image Velocimetry},
	booktitle = {Pattern Recognition -- 30th DAGM Symposium},
	volume = {5096},
	year = {2008},
	pages = {335--344},
	publisher = {Springer Verlag},
	organization = {Springer Verlag},
	author = {Florian Becker and Wieneke, Bernhard and Yuan, Jing and Christoph Schn{\"o}rr}
}
@conference {Becker-et-al-08b,
	title = {A Variational Approach to Adaptive Correlation for Motion Estimation in Particle Image Velocimetry},
	booktitle = {Pattern Recognition {\textendash} 30th DAGM Symposium},
	series = {lncs},
	volume = {5096},
	year = {2008},
	pages = {335{\textendash}344},
	publisher = {Springer Verlag},
	organization = {Springer Verlag},
	author = {Florian Becker and Wieneke, Bernhard and Yuan, Jing and Christoph Schn{\"o}rr}
}
@conference {becker_08_variational2,
	title = {Variational Correlation Approach to Flow Measurement with Window
Adaption},
	booktitle = {14th International Symposium on Applications of Laser Techniques
to Fluid Mechanics},
	year = {2008},
	note = {1},
	pages = {1.1.8},
	author = {Florian Becker and Wieneke, B. and Yuan, J. and Christoph Schn{\"o}rr}
}
@conference {Becker-et-al-08c,
	title = {Variational Correlation Approach to Flow Measurement with Window Adaption},
	booktitle = {14th International Symposium on Applications of Laser Techniques to Fluid Mechanics},
	year = {2008},
	pages = {1.1.3},
	author = {Florian Becker and Wieneke, Bernhard and Yuan, Jing and Christoph Schn{\"o}rr}
}
@conference {Becker-et-al-08c,
	title = {Variational Correlation Approach to Flow Measurement with Window Adaption},
	booktitle = {14th International Symposium on Applications of Laser Techniques to Fluid Mechanics},
	year = {2008},
	pages = {1.1.3},
	author = {Florian Becker and Wieneke, Bernhard and Yuan, Jing and Christoph Schn{\"o}rr}
}
@conference {Gosch-Fundana-Heyden-Schnoerr-2008,
	title = {View Point Tracking of Rigid Object Based on Shape Sub-Manifolds},
	booktitle = {Computer Vision -- ECCV 2008},
	volume = {5302},
	year = {2008},
	pages = {251--263},
	publisher = {Springer},
	organization = {Springer},
	author = {Gosch, Christian and Fundana, Ketut and Heyden, Anders and Christoph Schn{\"o}rr}
}
@conference {Gosch-Fundana-Heyden-Schnoerr-2008,
	title = {View Point Tracking of Rigid Object Based on Shape Sub-Manifolds},
	booktitle = {Computer Vision {\textendash} ECCV 2008},
	series = {lncs},
	volume = {5302},
	year = {2008},
	pages = {251{\textendash}263},
	publisher = {Springer},
	organization = {Springer},
	author = {Gosch, Christian and Fundana, Ketut and Heyden, Anders and Christoph Schn{\"o}rr}
}
@conference {kondermann2007,
	title = {An adaptive confidence measure for optical flows based on linear subspace projections},
	booktitle = {Proceedings of the 29th DAGM Symposium on Pattern Recognition},
	volume = {4713},
	year = {2007},
	pages = {132--141},
	publisher = {Springer},
	organization = {Springer},
	abstract = {Confidence measures are important for the validation of optical flow fields by estimating the correctness of each displacement vector. There are several frequently used confidence measures, which have been found of at best intermediate quality. Hence, we propose a new confidence measure based on linear subspace projections. The results are compared to the best previously proposed confidence measures with respect to an optimal confidence. Using the proposed measure we are able to improve previous results by up to 31\%.},
	doi = {10.1007/978-3-540-74936-3_14},
	author = {Claudia Kondermann and Daniel Kondermann and Bernd J{\"a}hne and Christoph S. Garbe and Christoph Schn{\"o}rr and Bernd J{\"a}hne},
	editor = {Fred A. Hamprecht}
}
@article {Yuan-et-al-jmiv-06,
	title = {Discrete Orthogonal Decomposition and Variational Fluid Flow Estimation},
	journal = {J.~Math.~Imag.~Vision},
	volume = {28},
	year = {2007},
	pages = {67-80},
	author = {Yuan, J. and Christoph Schn{\"o}rr and M{\'e}min, E.}
}
@article {Schellewald-et-al-07,
	title = {Evaluation of a convex relaxation to a quadratic assignment matching approach for relational object views},
	journal = {Image Vision Comp.},
	volume = {25},
	year = {2007},
	pages = {1301--1314},
	author = {Schellewald, C. and Roth, S. and Christoph Schn{\"o}rr}
}
@conference {garbe2007,
	title = {Fluid flow estimation through integration of physical flow configurations},
	booktitle = {Proceedings of the 29th DAGM Symposium on Pattern Recognition},
	year = {2007},
	pages = {92--101},
	publisher = {Springer},
	organization = {Springer},
	abstract = {The measurement of fluid flows is an emerging field for optical flow computation. In a number of such applications, a tracer is visualized with modern digital cameras. Due to the projective nature of the imaging process, the tracer is integrated across a velocity profile. In this contribution, a novel technique is presented that explicitly models brightness changes due to this integration. Only through this modeling is an accurate estimation of the flow velocities feasible. Apart from an accurate measurement of the fluid flow, also the underlying velocity profile can be reconstructed. Applications from shear flow, microfluidics and a biological applications are presented.},
	doi = {10.1007/978-3-540-74936-3_10},
	author = {Christoph S. Garbe and Christoph Schn{\"o}rr and Bernd J{\"a}hne},
	editor = {Fred A. Hamprecht}
}
@conference {Karim-et-al-07,
	title = {Greedy-Based Design of Sparse Two-Stage SVMs for Fast Classification},
	booktitle = {Pattern Recognition -- 29th DAGM Symposium},
	volume = {4713},
	year = {2007},
	pages = {395-404},
	publisher = {Springer},
	organization = {Springer},
	author = {Karim, R. and Bergtholdt, M. and J{\"o}rg H. Kappes and Christoph Schn{\"o}rr}
}
@article {Gall-et-al-07,
	title = {Interacting and Annealing Particle Filters: Mathematics and a Recipe for Applications},
	journal = {J.~Math.~Imag.~Vision},
	volume = {28},
	year = {2007},
	pages = {1--18},
	author = {Gall, J{\"u}rgen and Potthoff, J{\"u}rgen and Christoph Schn{\"o}rr and Rosenhahn, Bodo and Hans-Peter Seidel}
}
@article {Gall-et-al-07,
	title = {Interacting and Annealing Particle Filters: Mathematics and a Recipe for Applications},
	journal = {J. Math. Imag. Vision},
	volume = {28},
	year = {2007},
	pages = {1{\textendash}18},
	author = {Gall, J{\"u}rgen and Potthoff, J{\"u}rgen and Christoph Schn{\"o}rr and Rosenhahn, Bodo and Seidel, Hans-Peter}
}
@article {Welk-et-al-07,
	title = {Median and related local filters for tensor-valued images},
	journal = {Signal Processing},
	volume = {87},
	year = {2007},
	pages = {291-308},
	author = {Welk, M. and Weickert, J. and Florian Becker and Christoph Schn{\"o}rr and Feddern, C. and Burgeth, B.}
}
@article {Ruhnau-Schnoerr-EiF07,
	title = {Optical Stokes Flow Estimation: An Imaging-Based Control Approach},
	journal = {Exp.~in Fluids},
	volume = {42},
	year = {2007},
	pages = {61--78},
	author = {Paul Ruhnau and Christoph Schn{\"o}rr}
}
@proceedings {DAGM07,
	title = {Pattern Recognition {\textendash} 29th DAGM Symposium},
	volume = {4713},
	year = {2007},
	publisher = {Springer},
	editor = {Fred A. Hamprecht and Christoph Schn{\"o}rr and Bernd J{\"a}hne}
}
@book {hamprecht_07_pattern,
	title = {Pattern Recognition, 29th DAGM Symposium, Heidelberg, Germany, September 12-14, 2007, Proceedings},
	volume = {4713},
	year = {2007},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-540-74936-3},
	editor = {Fred A. Hamprecht and Bernd J{\"a}hne and Christoph Schn{\"o}rr}
}
@proceedings {hamprecht2007,
	title = {Pattern Recognition, 29th DAGM Symposium, Heidelberg, Germany, September 12-14},
	volume = {4713},
	year = {2007},
	publisher = {Springer},
	doi = {10.1007/978-3-540-74936-3},
	author = {Christoph Schn{\"o}rr and Bernd J{\"a}hne},
	editor = {Fred A. Hamprecht}
}
@conference {andres_07_selection,
	title = {Selection of Local Optical Flow Models by Means of Residual Analysis},
	booktitle = {Pattern Recognition},
	volume = {4713},
	year = {2007},
	note = {1},
	pages = {72-81},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-540-74936-3_8},
	author = {Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph S. Garbe},
	editor = {Christoph Schn{\"o}rr and Bernd J{\"a}hne and Fred A. Hamprecht}
}
@conference {andres2007,
	title = {Selection of local optical flow models by means of residual analysis},
	booktitle = {Proceedings of the 29th DAGM Symposium on Pattern Recognition},
	year = {2007},
	pages = {72--81},
	publisher = {Springer},
	organization = {Springer},
	abstract = {This contribution presents a novel approach to the challenging problem of model selection in motion estimation from sequences of images. New light is cast on parametric models of local optical flow. These models give rise to parameter estimation problems with highly correlated errors in variables (EIV). Regression is hence performed by equilibrated total least squares. The authors suggest to adaptively select motion models by testing local empirical regression residuals to be in accordance with the probability distribution that is theoretically predicted by the EIV model. Motion estimation with residual-based model selection is examined on artificial sequences designed to test specifically for the properties of the model selection process. These simulations indicate a good performance in the exclusion of inappropriate models and yield promising results in model complexity control.},
	doi = {10.1007/978-3-540-74936-3_8},
	author = {Bj{\"o}rn Andres and Christoph S. Garbe and Christoph Schn{\"o}rr and Bernd J{\"a}hne},
	editor = {Fred A. Hamprecht and Fred A. Hamprecht}
}
@conference {goerlitz_07_semi,
	title = {Semi-Supervised Tumor Detection in MRSI With Discriminative Random Fields},
	booktitle = {Pattern Recognition},
	volume = {4713},
	year = {2007},
	note = {1},
	pages = {224-233},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-540-74936-3_23},
	author = {G{\"o}rlitz, L. and Bjoern H. Menze and M.-A. Weber and B. Michael Kelm},
	editor = {Fred A. Hamprecht and Fred A. Hamprecht and Christoph Schn{\"o}rr and Bernd J{\"a}hne}
}
@article {Schnoerr-Computing-07,
	title = {Signal and Image Approximation with Level-Set Constraints},
	journal = {Computing},
	volume = {81},
	year = {2007},
	pages = {137-160},
	author = {Christoph Schn{\"o}rr}
}
@article {Yuan-et-al-SIAM07,
	title = {Simultaneous Optical Flow Estimation and Decomposition},
	journal = {SIAM J.~Scientific Computing},
	volume = {29},
	number = {6},
	year = {2007},
	pages = {2283-2304},
	author = {Yuan, J. and Christoph Schn{\"o}rr and Steidl, G.}
}
@conference {Schmidt-et-al-07,
	title = {Spine Detection and Labeling Using a Parts-Based Graphical Model},
	booktitle = {Proc. 20th International Conference on Information Processing in Medical Imaging (IPMI 2007)},
	volume = {4584},
	year = {2007},
	pages = {122-133},
	publisher = {Springer},
	organization = {Springer},
	author = {Schmidt, S. and J{\"o}rg H. Kappes and Bergtholdt, M. and Pekar, V. and Dries, S. and Bystrov, D. and Christoph Schn{\"o}rr}
}
@article {Ruhnau-et-al-MST07,
	title = {Variational Estimation of Experimental Fluid Flows with Physics-Based Spatio-Temporal Regularization},
	journal = {Measurement Science and Technology},
	volume = {18},
	year = {2007},
	pages = {755-763},
	author = {Paul Ruhnau and Stahl, A. and Christoph Schn{\"o}rr}
}
@conference {Weber-et-al-06b,
	title = {A Benchmark Evaluation of Large-Scale Optimization Approaches to Binary Tomography},
	booktitle = {Discrete Geometry for Computer Imagery (DGCI 2006)},
	volume = {4245},
	year = {2006},
	pages = {146-156},
	publisher = {Springer},
	organization = {Springer},
	author = {Weber, S. and Nagy, A. and Sch{\"u}le, T. and Christoph Schn{\"o}rr and Kuba, A.}
}
@conference {Weber-et-al-06a,
	title = {Binary Tomography with Deblurring},
	booktitle = {Combinatorial Image Analysis},
	volume = {4040},
	year = {2006},
	pages = {375-388},
	publisher = {Springer},
	organization = {Springer},
	author = {Weber, S. and Sch{\"u}le, T. and Christoph Schn{\"o}rr and Kuba, A.}
}
@conference {Heiler-Schnoerr-06a,
	title = {Controlling Sparseness in Non-negative Tensor Factorization},
	booktitle = {Computer Vision -- ECCV 2006},
	volume = {3951},
	year = {2006},
	pages = {56-67},
	publisher = {Springer},
	organization = {Springer},
	author = {Heiler, M. and Christoph Schn{\"o}rr}
}
@conference {StaRuhChr06,
	title = {A Distributed Parameter Approach to Dynamic Image Motion},
	booktitle = {ECCV 2006, International Workshop on The Representation and Use of Prior Knowledge in Vision},
	year = {2006},
	publisher = {LNCS, Springer},
	organization = {LNCS, Springer},
	author = {Stahl, A. and Paul Ruhnau and Christoph Schn{\"o}rr}
}
@conference {Bergtholdt-et-al-06b,
	title = {Learning of Graphical Models and Efficient Inference for Object Class Recognition},
	booktitle = {Proc. DAGM 2006},
	series = {LCNS},
	volume = {375-388},
	year = {2006},
	pages = {375-388},
	publisher = {Springer},
	organization = {Springer},
	author = {Bergtholdt, Martin and Kappes, J{\"o}rg H. and Christoph Schn{\"o}rr}
}
@article {Bruhn-et-al-06,
	title = {A Multigrid Platform for Real-Time Motion Computation with Discontinuity-Preserving Variational Methods},
	journal = {Int.~J.~Computer Vision},
	volume = {70},
	number = {3},
	year = {2006},
	pages = {257-277},
	author = {Bruhn, Andr{\'e}s and Weickert, Joachim and Kohlberger, Timo and Christoph Schn{\"o}rr}
}
@article {Bruhn-et-al-06,
	title = {A Multigrid Platform for Real-Time Motion Computation with Discontinuity-Preserving Variational Methods},
	journal = {Int. J. Computer Vision},
	volume = {70},
	number = {3},
	year = {2006},
	pages = {257-277},
	author = {Bruhn, Andr{\'e}s and Weickert, Joachim and Kohlberger, Timo and Christoph Schn{\"o}rr}
}
@article {Cremers-et-al-06,
	title = {Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentation},
	journal = {ijcv},
	volume = {66},
	number = {1},
	year = {2006},
	pages = {67-81},
	author = {Daniel Cremers and Sochen, Nir and Christoph Schn{\"o}rr}
}
@conference {Ruhnau-et-al-06a,
	title = {On-Line Variational Estimation of Dynamical Fluid Flows with Physics-Based Spatio-Temporal Regularization},
	booktitle = {Proc.~DAGM 2006},
	volume = {375-388},
	year = {2006},
	pages = {375-388},
	publisher = {Springer},
	organization = {Springer},
	author = {Paul Ruhnau and Stahl, A. and Christoph Schn{\"o}rr}
}
@conference {Bruhn-et-al-05a,
	title = {Discontinuity-Preserving Computation of Variational Optic Flow in Real-Time},
	booktitle = {Scale-Space 2005},
	series = {lncs},
	volume = {3459},
	year = {2005},
	pages = {279{\textendash}290},
	publisher = {Springer},
	organization = {Springer},
	author = {Bruhn, Andr{\'e}s and Weickert, Joachim and Kohlberger, Timo and Christoph Schn{\"o}rr}
}
@article {Weickert-et-al-03a,
	title = {Lucas/Kanade Meets Horn/Schunck: Combining Local and Global Optic Flow Methods},
	volume = {61},
	number = {3},
	year = {2005},
	pages = {211-231},
	author = {Bruhn, Andr{\'e}s and Weickert, Joachim and Christoph Schn{\"o}rr}
}
@conference {Welk-et-al-05a,
	title = {Matrix-Valued Filters as Convex Programs},
	booktitle = {Scale-Space 2005},
	series = {lncs},
	volume = {3459},
	year = {2005},
	pages = {204{\textendash}216},
	publisher = {Springer},
	organization = {Springer},
	author = {Welk, Martin and Florian Becker and Christoph Schn{\"o}rr and Weickert, Joachim}
}
@incollection {Bergtholdt-Schnoerr-05,
	title = {Shape Priors and Online Appearance Learning for Variational Segmentation and Object Recognition in Static Scenes},
	volume = {3663},
	year = {2005},
	pages = {342{\textendash}350},
	publisher = {Springer},
	author = {Bergtholdt, Martin and Christoph Schn{\"o}rr}
}
@conference {Yuan-et-al-05b,
	title = {A Study of Non-Smooth Convex Flow Decomposition},
	booktitle = {Proc. Variational, Geometric and Level Set Methods in Computer Vision},
	series = {lncs},
	volume = {3752},
	year = {2005},
	pages = {1{\textendash}12},
	publisher = {Springer},
	organization = {Springer},
	author = {Yuan, Jing and Christoph Schn{\"o}rr and Steidl, Gabriele and Florian Becker}
}
@article {Bruhn-et-al-4b,
	title = {Variational optic flow computation in real-time},
	journal = {IEEE Trans. Image Proc.},
	volume = {14},
	number = {5},
	year = {2005},
	pages = {608{\textendash}615},
	author = {Bruhn, Andr{\'e}s and Weickert, Joachim and Feddern, Christian and Kohlberger, Timo and Christoph Schn{\"o}rr}
}
@article {Ruhnau-et-al-05,
	title = {Variational Optical Flow Estimation for Particle Image Velocimetry},
	journal = {Experiments in Fluids},
	volume = {38},
	year = {2005},
	pages = {21--32},
	author = {Paul Ruhnau and Kohlberger, T. and Nobach, H. and Christoph Schn{\"o}rr}
}
@incollection {Bergtholdt-et-al-05,
	title = {Variational Segmentation with Shape Priors},
	year = {2005},
	pages = {147-160},
	publisher = {Springer},
	chapter = {9},
	author = {Bergtholdt, Martin and Daniel Cremers and Christoph Schn{\"o}rr},
	editor = {Paragios, N. and Chen, Y. and Faugeras, O.}
}
@article {Bruhn-et-al-04a,
	title = {High performance cluster computing with 3-D nonlinear diffusion filters},
	journal = {Real-Time Imaging},
	volume = {10},
	number = {1},
	year = {2004},
	pages = {41{\textendash}51},
	author = {Bruhn, Andr{\'e}s and Jakob, Tobias and Fischer, Markus and Weickert, Joachim and Br{\"u}ning, Ulrich and Christoph Schn{\"o}rr}
}
@conference {Cremers-et-al-04,
	title = {Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentation},
	booktitle = {Computer Vision {\textendash} ECCV 2004},
	series = {lncs},
	volume = {3024},
	year = {2004},
	pages = {74-86},
	publisher = {Springer},
	organization = {Springer},
	author = {Daniel Cremers and Sochen, Nir and Christoph Schn{\"o}rr},
	editor = {Pajdla, T. and Matas, J.}
}
@conference {Bruhn-et-al-03a,
	title = {Real-Time Optic Flow Computation with Variational Methods},
	booktitle = {Proc. Computer Analysis of Images and Patterns (CAIP{\textquoteright}03)},
	series = {LNCS},
	volume = {2756},
	year = {2003},
	pages = {222-229},
	publisher = {Springer},
	organization = {Springer},
	author = {Bruhn, Andr{\'e}s and Weickert, Joachim and Feddern, Christian and Kohlberger, Timo and Christoph Schn{\"o}rr},
	editor = {Petkov, N. and Westenberg, M.A.}
}
@article {Cremers-et-al-02c,
	title = {Shape Statistics in Kernel Space for Variational Image Segmentation},
	journal = {Pattern Recognition},
	volume = {36},
	number = {9},
	year = {2003},
	pages = {1929--1943},
	author = {Daniel Cremers and Kohlberger, Timo and Christoph Schn{\"o}rr}
}
@article {Cremers-et-al-02c,
	title = {Shape Statistics in Kernel Space for Variational Image Segmentation},
	journal = {Pattern Recognition},
	volume = {36},
	number = {9},
	year = {2003},
	pages = {1929{\textendash}1943},
	author = {Daniel Cremers and Kohlberger, Timo and Christoph Schn{\"o}rr}
}
@article {Cremers-Schnoerr-02d,
	title = {Statistical Shape Knowledge in Variational Motion Segmentation},
	journal = {Image and Vision Comp.},
	volume = {21},
	number = {1},
	year = {2003},
	pages = {77-86},
	author = {Daniel Cremers and Christoph Schn{\"o}rr}
}
@conference {Cremers-Sochen-Schnoerr-03a,
	title = {Towards Recognition-Based Variational Segmentation Using Shape Priors and Dynamic Labeling},
	booktitle = {Scale Space Methods in Computer Vision},
	volume = {2695},
	year = {2003},
	pages = {388--400},
	publisher = {Springer},
	organization = {Springer},
	author = {Daniel Cremers and Sochen, Nir and Christoph Schn{\"o}rr},
	editor = {Griffin, L.D. and Lillholm, M.}
}
@conference {Cremers-Sochen-Schnoerr-03a,
	title = {Towards Recognition-Based Variational Segmentation Using Shape Priors and Dynamic Labeling},
	booktitle = {Scale Space Methods in Computer Vision},
	series = {LNCS},
	volume = {2695},
	year = {2003},
	pages = {388{\textendash}400},
	publisher = {Springer},
	organization = {Springer},
	author = {Daniel Cremers and Sochen, Nir and Christoph Schn{\"o}rr},
	editor = {Griffin, L.D. and Lillholm, M.}
}
@techreport {Bruhn-et-al-03b,
	title = {Variational Optic Flow Computation in Real-Time},
	number = {89},
	year = {2003},
	note = {\em IEEE Trans. Image Processing\/, revised and resubmitted},
	month = {May},
	institution = {Dept. Math. and Comp. Science},
	type = {Fachrichtung 6.1 {\textendash} Mathematik, Technical Report},
	address = {Saarland University, Germany},
	author = {Bruhn, Andr{\'e}s and Weickert, Joachim and Feddern, Christian and Kohlberger, Timo and Christoph Schn{\"o}rr}
}
@article {Hinterberger-et-al-02,
	title = {Analysis of Optical Flow Models in the Framework of Calculus of Variations},
	journal = {Numer. Funct. Anal. Optimiz.},
	volume = {23},
	number = {1/2},
	year = {2002},
	pages = {69{\textendash}89},
	author = {Hinterberger, Walter and Scherzer, Otmar and Christoph Schn{\"o}rr and Weickert, Joachim}
}
@conference {Bruhn-et-al-02b,
	title = {Combining the Advantages of Local and Global Optic Flow Methods},
	booktitle = {Pattern Recognition, Proc. 24th DAGM Symposium},
	series = {lncs},
	volume = {2449},
	year = {2002},
	pages = {454{\textendash}462},
	publisher = {Springer},
	organization = {Springer},
	address = {Z{\"u}rich, Switzerland},
	author = {Bruhn, Andr{\'e}s and Weickert, Joachim and Christoph Schn{\"o}rr},
	editor = {van Gool, L.}
}
@conference {Bruhn-et-al-02a,
	title = {Designing 3{\textendash}D Nonlinear Diffusion Filters for High Performance Cluster Computing},
	booktitle = {Pattern Recognition, Proc. 24th DAGM Symposium},
	series = {lncs},
	volume = {2449},
	year = {2002},
	pages = {290{\textendash}297},
	publisher = {Springer},
	organization = {Springer},
	address = {Z{\"u}rich, Switzerland},
	author = {Bruhn, Andr{\'e}s and Jakob, Tobias and Fischer, Markus and Kohlberger, Timo and Weickert, Joachim and Br{\"u}ning, Ulrich and Christoph Schn{\"o}rr},
	editor = {van Gool, L.}
}
@article {Cremers-et-al-02b,
	title = {Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford{\textendash}Shah functional},
	journal = {Int. J. Computer Vision},
	volume = {50},
	number = {3},
	year = {2002},
	pages = {295{\textendash}313},
	author = {Daniel Cremers and Tischh{\"a}user, Florian and Weickert, Joachim and Christoph Schn{\"o}rr}
}
@conference {Cremers-Schnoerr-02,
	title = {Motion Competition: Variational Integration of Motion Segmentation and Shape Regularization},
	booktitle = {Pattern Recognition, Proc. 24th DAGM Symposium},
	series = {lncs},
	volume = {2449},
	year = {2002},
	pages = {472{\textendash}480},
	publisher = {Springer},
	organization = {Springer},
	address = {Z{\"u}rich, Switzerland},
	author = {Daniel Cremers and Christoph Schn{\"o}rr},
	editor = {van Gool, L.}
}
@conference {Cremers-et-al-02a,
	title = {Nonlinear Shape Statistics in Mumford-Shah Based Segmentation},
	booktitle = {Computer Vision -- ECCV 2002)},
	volume = {2351},
	year = {2002},
	pages = {93--108},
	publisher = {Springer Verlag},
	organization = {Springer Verlag},
	author = {Daniel Cremers and Kohlberger, Timo and Christoph Schn{\"o}rr},
	editor = {Heyden, A. and Sparr, G. and Johansen, P. and Nielsen, M.}
}
@conference {Cremers-et-al-02a,
	title = {Nonlinear Shape Statistics in Mumford-Shah Based Segmentation},
	booktitle = {Computer Vision {\textendash} ECCV 2002)},
	series = {lncs},
	volume = {2351},
	year = {2002},
	pages = {93{\textendash}108},
	publisher = {Springer Verlag},
	organization = {Springer Verlag},
	author = {Daniel Cremers and Kohlberger, Timo and Christoph Schn{\"o}rr},
	editor = {Heyden, A. and Sparr, G. and Nielsen, M. and Johansen, P.}
}
@conference {Cremers-et-al-01a,
	title = {Diffusion{\textendash}Snakes: Combining Statistical Shape Knowledge and Image Information in a Variational Framework},
	booktitle = {IEEE First Workshop on Variational and Level Set Methods in Computer Vision},
	year = {2001},
	pages = {237{\textendash}244},
	publisher = {IEEE Comp. Soc.},
	organization = {IEEE Comp. Soc.},
	address = {Vancouver, Canada},
	author = {Daniel Cremers and Christoph Schn{\"o}rr and Weickert, Joachim}
}
@conference {Cremers-et-al-01b,
	title = {Nonlinear Shape Statistics via Kernel Spaces},
	booktitle = {Mustererkennung 2001},
	volume = {2191},
	year = {2001},
	pages = {269--276},
	publisher = {Springer},
	organization = {Springer},
	author = {Daniel Cremers and Kohlberger, Timo and Christoph Schn{\"o}rr},
	editor = {B. Radig and S. Florczyk}
}
@conference {Cremers-et-al-01b,
	title = {Nonlinear Shape Statistics via Kernel Spaces},
	booktitle = {Mustererkennung 2001},
	series = {Lect. Notes Comp. Science},
	volume = {2191},
	year = {2001},
	month = {Sept. 12{\textendash}14},
	pages = {269{\textendash}276},
	publisher = {Springer},
	organization = {Springer},
	address = {Munich, Germany},
	author = {Daniel Cremers and Kohlberger, Timo and Christoph Schn{\"o}rr},
	editor = {Radig, B. and Florczyk, S.}
}
@conference {Cremers-et-al-00a,
	title = {Diffusion Snakes Using Statistical Shape Knowledge},
	booktitle = {Proc. Algebraic Frames for the Perception-Action Cycle},
	series = {lncs},
	volume = {1888},
	year = {2000},
	month = {Sept. 10-11},
	pages = {164{\textendash}174},
	publisher = {Springer},
	organization = {Springer},
	address = {Kiel},
	author = {Daniel Cremers and Christoph Schn{\"o}rr and Weickert, Joachim and Schellewald, Christian},
	editor = {Sommer, G. and Zeevi, Y.}
}
@conference {Cremers-et-al-00b,
	title = {Learning Translation Invariant Shape Knowledge for Steering Diffusion-Snakes},
	booktitle = {3rd Workshop on Dynamic Perception},
	series = {Proc. in Artificial Intelligence},
	volume = {9},
	year = {2000},
	pages = {117{\textendash}122},
	publisher = {Akad. Verlagsges.},
	organization = {Akad. Verlagsges.},
	address = {Berlin, Germany},
	author = {Daniel Cremers and Christoph Schn{\"o}rr and Weickert, Joachim and Schellewald, Christian},
	editor = {Baratoff, G. and Neumann, H.}
}
@conference {Fornland-Schnoerr-97,
	title = {Determining the Dominant Plane from Uncalibrated Stereo Vision by a Robust and Convergent Iterative Approach without Correspondence},
	booktitle = {Proc. Int. Conf. Comp. Vision and Patt. Recog. (CVPR{\textquoteright}97)},
	year = {1997},
	month = {June 17-19},
	address = {San Juan, Puerto Rico},
	author = {Fornland, P{\"a}r and Christoph Schn{\"o}rr}
}
@article {Rohr-Schnoerr-ivc-93,
	title = {An Efficient Approach to the Identification of Characteristic Intensity Variations},
	volume = {11},
	number = {5},
	year = {1993},
	pages = {273{\textendash}277},
	author = {Rohr, Karl and Christoph Schn{\"o}rr}
}
