Publications
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(2002). Designing 3--D Nonlinear Diffusion Filters for High Performance Cluster Computing. Pattern Recognition, Proc.~24th DAGM Symposium. Springer. 2449 290--297
(2002). Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford--Shah functional. Int.~J.~Computer Vision. 50 295--313
(2002). Motion Competition: Variational Integration of Motion Segmentation and Shape Regularization. Pattern Recognition, Proc.~24th DAGM Symposium. Springer. 2449 472--480
(2002). Nonlinear Shape Statistics in Mumford-Shah Based Segmentation. Computer Vision -- ECCV 2002). Springer Verlag. 2351 93--108
Technical Report (636.58 KB)
Technical Report (636.58 KB) (2002). Performance Evaluation Of A Convex Relaxation Approach To The Quadratic Assignment Of Relational Object Views. Dept.~Math.~and Comp.~Science
(2002). Unsupervised Image Partitioning with Semidefinite Programming. Pattern Recognition, Proc.~24th DAGM Symposium. Springer. 2449 141--149
(2001). A 1D analog VLSI implementation for non-linear real-time signal preprocessing. Real--Time Imaging. 7 127--142
(2001). Application Of Convex Optimization Techniques To The Relational Matching Of Object Views. Dept.~Math.~and Comp.~Science
(2001). Convex Relaxations for Binary Image Partitioning and Perceptual Grouping. Mustererkennung 2001. Springer. 2191 353--360
(2001). Diffusion--Snakes: Combining Statistical Shape Knowledge and Image Information in a Variational Framework. IEEE First Workshop on Variational and Level Set Methods in Computer Vision. IEEE Comp.~Soc. 237--244
(2001). Efficient Feature Subset Selection For Support Vector Machines. Dept.~Math.~and Comp.~Science
(2001). Evaluation of Convex Optimization Techniques for the Weighted Graph--Matching Problem in Computer Vision. Mustererkennung 2001. Springer. 2191 361--368
(2001). Fast parallel algorithms for a broad class of nonlinear variational diffusion approaches. Real--Time Imaging. 7 31--45
(2001). Globally--Convergent Iterative Numerical Schemes for Non--Linear Variational Image Smoothing and Segmentation on a Multi--Processor Machine. IEEE Trans.~Image Proc. 10 852--864
(2001). Image labeling and grouping by minimizing linear functionals over cones. Proc.~Third Int. Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'01). Springer. 2134 267--282
(2001). Nonlinear Shape Statistics via Kernel Spaces. Mustererkennung 2001. Springer. 2191 269--276 Technical Report (324.55 KB)
Technical Report (324.55 KB) (2001). Statistische Mustererkennung
(2001). A Theoretical Framework for Convex Regularizers in PDE--Based Computation of Image Motion. Int.~J.~Computer Vision. 45 245--264
(2001). Variational Optic Flow Computation with a Spatio-Temporal Smoothness Constraint. J.~Math.~Imaging and Vision. 14 245--255
(2000). On the computational rôle of the primate retina. Proc.~2nd ICSC Symposium on Neural Computation (NC 2000)
(2000). Diffusion Snakes Using Statistical Shape Knowledge. Proc.~Algebraic Frames for the Perception-Action Cycle. Springer. 1888 164--174
(2000). Learning Translation Invariant Shape Knowledge for Steering Diffusion-Snakes. 3rd Workshop on Dynamic Perception. Akad.~Verlagsges. 9 117--122
(2000). Variational Adaptive Smoothing and Segmentation. Computer Vision and Applications: A Guide for Students and Practitioners. Academic Press. 459--482
(2000). Variational Image Motion Computation: Theoretical Framework, Problems and Perspectives. Mustererkennung 2000. Springer
(1999). Investigating A Class Of Iterative Schemes And Their Parallel Implementation For Nonlinear Variational Image Smoothing And Segmentation. Comp.~Sci.~Dept., AB KOGS
(1999). A model of spatiotemporal receptive fields in the primate retina. Proc.~1st Göttingen Conf.~German Neurosci.~Soc.. II
(1999). Modeling spatiotemporal receptive fields in the primate retina. Proc.~Cognitive Neurosci.~Conf
(1999). Parameter-Free Elastic Deformation Approach for 2D and 3D Registration Using Prescribed Displacements. J.~Math.~Imaging and Vision. 10 143--162
(1999). Räumlich--zeitliche Berechnung des optischen Flusses mit nichtlinearen flussabhängigen Glattheitstermen. Mustererkennung 1999. Springer. 317--324
(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
(1998). A class of parallel algorithms for nonlinear variational image segmentation. Proc.~Noblesse Workshop on Non--Linear Model Based Image Analysis (NMBIA'98)
(1998). Dynamic Circular Cellular Networks for Adaptive Smoothing of Multi--Dimensional Signals. Proc.~5th IEEE Int.~Workshop on Cellular Neural Networks and their Applications
(1998). Investigation of Parallel and Globally Convergent Iterative Schemes for Nonlinear Variational Image Smoothing and Segmentation. Proc.~IEEE Int.~Conf.~Image Proc