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2008
J. Yuan, Steidl, G., and Schnörr, C., “Convex Hodge Decomposition of Image Flows”, in Pattern Recognition -- 30th DAGM Symposium, 2008, vol. 5096, p. 416--425.PDF icon Technical Report (290.72 KB)
J. Lellmann, Kappes, J. H., Yuan, J., Becker, F., and Schnörr, C., “Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation”, IWR, University of Heidelberg, 2008.PDF icon Technical Report (2.6 MB)
F. Becker and Schnörr, C., “Decomposition of Quadratric Variational Problems”, in Pattern Recognition -- 30th DAGM Symposium, 2008, vol. 5096, p. 325--334.PDF icon Technical Report (1.29 MB)
F. Becker and Schnörr, C., “Decomposition of Quadratric Variational Problems”, in Pattern Recognition -- 30th DAGM Symposium, 2008, vol. 5096, p. 325--334.
J. A. J. Steen, Steen, H., Georgi, A., Parker, K. C., Springer, M., Kirchner, M., Hamprecht, F. A., and Kirschner, M. W., “Different Phosphorylation States of the Anaphase Promoting Complex in Response to Anti-Mitotic Drugs: A Quantitative Proteomic Analysis”, Proceedings of the National Academy of Sciences, vol. 105, pp. 6069-6074, 2008.PDF icon Technical Report (173.02 KB)
J. Scholz, Wiersbinski, T., Ruhnau, P., Kondermann, D., Garbe, C. S., Hain, R., and Beushausen, V., “Double-pulse planar-LIF investigations using fluorescence motion analysis for mixture formation investigation”, Exp. Fluids, vol. 45, p. 583--593, 2008.
S. Petra, Popa, C., and Schnörr, C., “Enhancing Sparsity by Constraining Strategies: Constrained SIRT versus Spectral Projected Gradient Methods”, in Proc. 7th Workshop on Modelling of Environmental and Life Sciences Problems (WMM 08), Constanta, Romania, 2008.
S. Petra, Popa, C., and Schnörr, C., “Enhancing Sparsity by Constraining Strategies: Constrained SIRT versus Spectral Projected Gradient Methods”, in Proc. 7th Workshop on Modelling of Environmental and Life Sciences Problems (WMM 08), Bucharest, Romania, 2008.
K. E. Richter, “Ermittlung der Leckraten der WiSSCy-Messkampagne 2007 in Hamburg mittels UV-Spektroskopie”, Institut für Umweltphysik, Universität Heidelberg, 2008.
B. Andres, Kondermann, C., Kondermann, D., Köthe, U., Hamprecht, F. A., and Garbe, C. S., “On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation”, Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on, pp. 1-6, 2008.PDF icon Technical Report (1.58 MB)
B. Andres, Kondermann, C., Kondermann, D., Hamprecht, F. A., and Garbe, C. S., “On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation”, in IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, 2008, p. 1--6.
S. Petra, Popa, C., and Schnörr, C., “Extended and Constrained Cimmino-type Algorithms with Applications in Tomographic Image Reconstruction”, IWR, University of Heidelberg, 2008.PDF icon Technical Report (2.13 MB)
S. Petra, Popa, C., and Schnörr, C., “Extended and Constrained Cimmino-type Algorithms with Applications in Tomographic Image Reconstruction”, IWR, University of Heidelberg, 2008.
L. Torresani, Kolmogorov, V., and Rother, C., “Feature correspondence via graph matching: Models and global optimization”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2008, vol. 5303 LNCS, pp. 596–609.
L. Torresani, Kolmogorov, V., and Rother, C., “Feature correspondence via graph matching: Models and global optimization”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2008, vol. 5303 LNCS, pp. 596–609.
V. Lempitsky, Roth, S., and Rother, C., “FusionFlow: Discrete-continuous optimization for optical flow estimation”, in 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2008.
S. Vicente, Kolmogorov, V., and Rother, C., “Graph cut based image segmentation with connectivity priors”, in 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2008.
A. Haja, “Graph-based Spatial Motion Tracking using Affine-covariant Regions”. IWR, Fakultät für Mathematik und Informatik, Univ.\ Heidelberg, 2008.
C. Rhemann, Rother, C., Rav-Acha, A., and Sharp, T., “High resolution matting via interactive trimap segmentation”, in 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2008.
C. Rhemann, Rother, C., Rav-Acha, A., and Sharp, T., “High resolution matting via interactive trimap segmentation”, in 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2008.
C. Rhemann, Rother, C., Rav-Acha, A., and Sharp, T., “High resolution matting via interactive trimap segmentation”, in 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2008.
M. Schmidt, “How to perform camera measurements according to the EMVA 1288 Standard.”. 2008.
V. Lempitsky, Blake, A., and Rother, C., “Image segmentation by branch-and-mincut”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2008, vol. 5305 LNCS, pp. 15–29.
V. Lempitsky, Blake, A., and Rother, C., “Image segmentation by branch-and-mincut”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2008, vol. 5305 LNCS, pp. 15–29.
C. Rhemann, Rother, C., and Gelautz, M., “Improving color modeling for alpha matting”, in BMVC 2008 - Proceedings of the British Machine Vision Conference 2008, 2008.
J. F. Acker, Berkels, B., Bredies, K., Diallo, M. S., Droske, M., Garbe, C. S., Holschneider, M., Hron, J., Kondermann, C., Kulesh, M., Maass, P., Olischläger, N., and Peitgen, H. - O., “Inverse Problems and Parameter Identification in Image Processing”, Mathematical Methods in Time Series Analysis and Digital Image Processing. Springer, p. 111--151, 2008.
B. Jähne, “Kameraauswahl nach objektiven Kriterien - Der EMVA1288 Kamerastandard”. 2008.
A. Haja, Jähne, B., and Abraham, S., “Localization accuracy of region detectors”, in Proceedings CVPR'08, 2008.
J. H. Kappes and Schnörr, C., “MAP-Inference for Highly-Connected Graphs with DC-Programming”, in Pattern Recognition -- 30th DAGM Symposium, 2008, vol. 5096, p. 1--10.PDF icon Technical Report (1.91 MB)
J. H. Kappes and Schnörr, C., “MAP-Inference for Highly-Connected Graphs with DC-Programming”, in Pattern Recognition – 30th DAGM Symposium, 2008, vol. 5096, pp. 1–10.
C. S. Garbe, Schimpf, U., and Jähne, B., “Measuring momentum transport directly at the air water interface from active infrared thermography”, in Geophysical Research Abstracts, 2008.
M. Staudacher, Hamprecht, F. A., and Görlitz, L., “Method for processing an intensity image of a microscope”, Patent, Patent Number: WO2008034721A1, 2008.PDF icon Technical Report (39.81 KB)
K. Roetmann, Schmunk, W., Garbe, C. S., and Beushausen, V., “Micro-flow analysis by molecular tagging velocimetry and planar raman-scattering”, Exp. Fluids, vol. 44, p. 419--430, 2008.
B. H. Menze, Kelm, B. Michael, Weber, M. - A., Bachert, P., and Hamprecht, F. A., “Mimicking the human expert: pattern recognition for an automated assessment of data quality in MRSI”, Magnetic Resonance in Medicine, vol. 59, pp. 1457-1466, 2008.PDF icon Technical Report (1.45 MB)
M. Enzweiler and Gavrila, D. M., “A Mixed Generative-Discriminative Framework for Pedestrian Classification”, in Proc. Int. Conf. Comp. Vision and Patt. Recog. (CVPR), 2008.

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