Publications

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Techreport
Bruhn, A, Weickert, J, Feddern, C, Kohlberger, T and Schnörr, C (2003). Variational Optic Flow Computation In Real-Time. Dept. Math. and Comp. Science, Saarland University, Germany
Petra, S and Schnörr, C (2009). Tomopiv Meets Compressed Sensing. IWR, University of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/9760PDF icon Technical Report (646.75 KB)
Lellmann, J, Lenzen, F and Schnörr, C (2011). Optimality Bounds For A Variational Relaxation Of The Image Partitioning Problem. IPA group, Heidelberg University. http://arxiv.org/abs/1112.0974
Nicola, A, Petra, S, Popa, C and Schnörr, C (2009). On A General Extending And Constraining Procedure For Linear Iterative Methods. IWR, University of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/9761PDF icon Technical Report (799.47 KB)
Petra, S, Popa, C and Schnörr, C (2008). Extended And Constrained Cimmino-Type Algorithms With Applications In Tomographic Image Reconstruction. IWR, University of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/8798/
Petra, S, Popa, C and Schnörr, C (2008). Extended And Constrained Cimmino-Type Algorithms With Applications In Tomographic Image Reconstruction. IWR, University of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/8798/PDF icon Technical Report (2.13 MB)
Lellmann, J, Kappes, J H, Yuan, J, Becker, F and Schnörr, C (2008). Convex Multi-Class Image Labeling By Simplex-Constrained Total Variation. IWR, University of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/8759/PDF icon Technical Report (2.6 MB)
Petra, S, Popa, C and Schnörr, C (2009). Accelerating Constrained Sirt With Applications In Tomographic Particle Image Reconstruction. IWR, University of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/9477PDF icon Technical Report (3.33 MB)
Journal Article
Becker, F, Lenzen, F, Kappes, J H and Schnörr, C (2013). Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences. International Journal of Computer Vision. Springer US. 105 269--297. http://dx.doi.org/10.1007/s11263-013-0639-7PDF icon Technical Report (15.4 MB)
Becker, F, Lenzen, F, Kappes, J H and Schnörr, C (2013). Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences. International Journal of Computer Vision. 105 (3) 269-297
Becker, F, Lenzen, F, Kappes, J H and Schnörr, C (2013). Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences. International Journal of Computer Vision. Springer US. 105 269–297. http://dx.doi.org/10.1007/s11263-013-0639-7
Ruhnau, P, Kohlberger, T, Nobach, H and Schnörr, C (2005). Variational Optical Flow Estimation for Particle Image Velocimetry. Experiments in Fluids. 38 21--32PDF icon Technical Report (1.21 MB)
Bruhn, A, Weickert, J, Feddern, C, Kohlberger, T and Schnörr, C (2005). Variational optic flow computation in real-time. IEEE Trans. Image Proc. 14 608–615
Heitz, D, Mémin, E and Schnörr, C (2010). Variational fluid flow measurements from image sequences: synopsis and perspectives. Exp.~Fluids. 48 369-393PDF icon Technical Report (1.91 MB)
Ruhnau, P, Stahl, A and Schnörr, C (2007). Variational Estimation of Experimental Fluid Flows with Physics-Based Spatio-Temporal Regularization. Measurement Science and Technology. 18 755-763PDF icon Technical Report (842.06 KB)
Becker, F, Wieneke, B, Petra, S, Schröder, A and Schnörr, C (2012). Variational Adaptive Correlation Method for Flow Estimation. IEEE Transactions on Image Processing. 21 3053 – 3065
Becker, F, Wieneke, B, Petra, S, Schröder, A and Schnörr, C (2012). Variational Adaptive Correlation Method for Flow Estimation. IEEE Transactions on Image Processing. 21 3053 -- 3065PDF icon Technical Report (18.81 MB)
Becker, F, Wieneke, B, Petra, S, Schröder, A and Schnörr, C (2011). Variational Adaptive Correlation Method for Flow Estimation. IEEE Transactions on Image Processing. 21, 6 3053 - 3065
Petra, S and Schnörr, C (2009). TomoPIV meets Compressed Sensing. Pure Math.~Appl. 20 49 -- 76. http://www.mat.unisi.it/newsito/puma/public_html/contents.phpPDF icon Technical Report (409.1 KB)
Bergtholdt, M, Kappes, J H, Schmidt, S and Schnörr, C (2010). A Study of Parts-Based Object Class Detection Using Complete Graphs. Int.~J.~Comp.~Vision. 87 93-117. http://www.springerlink.com/openurl.asp?genre=article&id=doi:10.1007/s11263-009-0209-1PDF icon Technical Report (2.18 MB)
Bergtholdt, M, Kappes, J H, Schmidt, S and Schnörr, C (2010). A Study of Parts-Based Object Class Detection Using Complete Graphs. Int. J. Comp. Vision. 87 93-117. http://www.springerlink.com/openurl.asp?genre=article&id=doi:10.1007/s11263-009-0209-1
Savchynskyy, B, Kappes, J H, Schmidt, S and Schnörr, C (2011). A Study of Nesterov's Scheme for Lagrangian Decomposition and MAP Labeling. IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), accepted as oral presentation. 1817 - 1823
Cremers, D and Schnörr, C (2003). Statistical Shape Knowledge in Variational Motion Segmentation. Image and Vision Comp. 21 77-86
Breitenreicher, D, Lellmann, J and Schnörr, C (2011). Sparse Template-Based Variational Image Segmentation. Advances in Adaptive Data Analysis. 3 149-166
Breitenreicher, D, Lellmann, J and Schnörr, C (2011). Sparse Template-Based Variational Image Segmentation. Advances in Adaptive Data Analysis. 3 149-166PDF icon Technical Report (866.28 KB)
Lenzen, F, Lellmann, J, Becker, F and Schnörr, C (2014). Solving QVIs for Image Restoration with Adaptive Constraint Sets. SIAM Journal on Imaging Sciences (SIIMS), in press
Lenzen, F, Lellmann, J, Becker, F and Schnörr, C (2014). Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets. SIAM J.~Imag.~Sci. 7 2139--2174PDF icon Technical Report (802.13 KB)
Yuan, J, Schnörr, C and Steidl, G (2007). Simultaneous Optical Flow Estimation and Decomposition. SIAM J.~Scientific Computing. 29 2283-2304PDF icon Technical Report (1.16 MB)

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