Publications

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Schnörr, (1989). Zur Schätzung von Geschwindigkeitsvektorfeldern in Bildfolgen mit einer richtungsabhängigen Glattheitsforderung. Mustererkennung 1989, 11. DAGM-Symposium. Springer-Verlag. 219 294--301
Schnörr, (1996). Repräsentation von Bilddaten mit einem konvexen Variationsansatz. Mustererkennung 1996. Springer-Verlag. 21--28
Schnörr, (2000). Variational Adaptive Smoothing and Segmentation. Computer Vision and Applications: A Guide for Students and Practitioners. Academic Press. 459--482
Schnörr, (1999). Variational Methods for Adaptive Image Smoothing and Segmentation. Handbook on Computer Vision and Applications: Signal Processing and Pattern Recognition. Academic Press. 2 451--484
Schnörr, (1994). Bewegungssegmentation von Bildfolgen durch die Minimierung konvexer nicht-quadratischer Funktionale. Mustererkennung 1994. Technische Universität Wien. 5 178--185
Schnörr, (2007). Signal and Image Approximation with Level-Set Constraints. Computing. 81 137-160PDF icon Technical Report (506.8 KB)
Schnörr, (2001). Statistische Mustererkennung
Schnörr, (1998). Variational approaches to Image Segmentation and Feature Extraction. University of Hamburg, Comp.~Sci.~Dept.
Schnörr, (1998). A Study of a Convex Variational Diffusion Approach for Image Segmentation and Feature Extraction. J. of Math. Imag. and Vision. 8 271--292
Schnörr, (1996). Representation Of Images By A Convex Variational Diffusion Approach. FB Informatik
Schnörr, (1994). Segmentation of Visual Motion by Minimizing Convex Non-Quadratic Functionals. 12th Int. Conf. on Pattern Recognition
Schnörr, (1994). Unique Reconstruction of Piecewise Smooth Images by Minimizing Strictly Convex Non-Quadratic Functionals. JMIV. 4 189--198
Schnörr, (1993). On Functionals with Greyvalue-Controlled Smoothness Terms for Determining Optical Flow. PAMI. 15 1074--1079
Schnörr, (1992). Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization. IJCV. 8 153--165
Schnörr, (1991). Funktionalanalytische Methoden zur Bestimmung von Bewegungsinformation aus TV-Bildfolgen. Fakultät für Informatik, Universität Karlsruhe (TH)
Schnörr, (1991). Determining Optical Flow for Irregular Domains by Minimizing Quadratic Functionals of a Certain Class. IJCV. 6 25--38
Schnörr, (1990). Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization. Proc. British Machine Vision Conference. 109--114
Schnörr, C and Neumann, B (1992). Ein Ansatz zur effizienten und eindeutigen Rekonstruktion stückweise glatter Funktionen. Mustererkennung 1992, 14. DAGM-Symposium. Springer-Verlag. 411--416
Schnörr, C, Niemann, H and Kopecz, J (1993). Architekturkonzepte zur Bildauswertung. Grundlagen und Anwendungen der Künstlichen Intelligenz, 17. Fachtagung für Künstliche Intelligenz. Springer-Verlag. 268--274
Schnörr, C and Peckar, W (1995). Motion-Based Identification of Deformable Templates. Proc. 6th Int. Conf. on Computer Analysis of Images and Patterns (CAIP '95). Springer Verlag. 970 122-129
Schnörr, C, Schüle, T and Weber, S (2007). Variational Reconstruction with DC-Programming. Advances in Discrete Tomography and Its Applications. Birkhäuser
Schnörr, C and Sprengel, R (1994). A Nonlinear Regularization Approach to Early Vision. Biol. Cybernetics. 72 141--149
Schnörr, C, Sprengel, R and Neumann, B (1996). A Variational Approach to the Design of Early Vision Algorithms. Computing Suppl. 11 149-165
Schnörr, C, Stiehl, H S and Grigat, R - R (1996). On Globally Asymptotically Stable Continuous-Time CNNs for Adaptive Smoothing of Multidimensional Signals. Proc. 4th IEEE Int. Workshop on Cellular Neural Networks and their Applications
Schnörr, C and Weickert, J (2000). Variational Image Motion Computation: Theoretical Framework, Problems and Perspectives. Mustererkennung 2000. Springer
Schnörr, (1996). Convex Variational Segmentation of Multi-Channel Images. Proc. 12th Int. Conf. on Analysis and Optimization of Systems: Images, Wavelets and PDE's. Springer-Verlag. 219
(2000). Künstliche Intelligenz: Special Issue on Medical Computer Vision. 3