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2011
F. Becker, Lenzen, F., Kappes, J. H., and Schnörr, C., “Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences”, in 2011 IEEE International Conference on Computer Vision ICCV, 2011, pp. 1692-1699.
2010
S. Vicente, Kolmogorov, V., and Rother, C., “Cosegmentation revisited: Models and optimization”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010, vol. 6312 LNCS, pp. 465–479.
B. Voss, Heinlein, A., Jähne, B., and Garbe, C. S., “A new approach for 3C3D measurements of aqueous boundary layer flows relative to the wind-wave undulated interface”, in 6th Int. Symp. Gas Transfer at Water Surfaces, Kyoto, May 17--21, 2010, 2010.
B. Voss and Garbe, C. S., “Novel strategy for water sided interfacial 3D3Cflow-visualization using a single camera”, in 14th International Symposium on Flow Visualization, 2010, pp. D1-018.
A. Vlasenko and Schnörr, C., “Physically Consistent and Efficient Variational Denoising of Image Fluid Flow Estimates”, IEEE Trans.~Image Proc., vol. 19, pp. 586-595, 2010.PDF icon Technical Report (2.65 MB)
A. Vlasenko and Schnörr, C., “Physically Consistent and Efficient Variational Denoising of Image Fluid Flow Estimates”, IEEE Trans. Image Proc., vol. 19, pp. 586-595, 2010.
A. Mansfield, Gehler, P., Van Gool, L., and Rother, C., “Scene carving: Scene consistent image retargeting”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010, vol. 6311 LNCS, pp. 143–156.
2009
F. Lauer, Bloch, G., and Vidal, R., “A Continuous Optimization Framework for Hybrid System Identification”, in submitted to Automatica, 2009.
C. Thieke, Nix, O., Koehn, A., Floca, R., van Straaten, D., Hahn, H., Strauss, L. G., Siems, U., Graf, M., Pruem, H., Klein, J., Laue, H., and Kaster, F. O., “A framework and multi-application prototype for integrated radiological diagnostics and radiation therapy”, Strahlentherapie und Onkologie, vol. 185, p. 81, 2009.
S. Vicente, Kolmogorov, V., and Rother, C., “Joint optimization of segmentation and appearance models”, in Proceedings of the IEEE International Conference on Computer Vision, 2009, pp. 755–762.
A. Vlasenko and Schnörr, C., “Variational Approaches for Model-Based PIV and Visual Fluid Analysis”, Imaging Measurement Methods for Flow Analysis, vol. 106. Springer, pp. 247-256, 2009.PDF icon Technical Report (3.39 MB)
A. Vlasenko and Schnörr, C., “Variational Approaches for Model-Based PIV and Visual Fluid Analysis”, Imaging Measurement Methods for Flow Analysis, vol. 106. Springer, pp. 247-256, 2009.
2008
B. Voss, “Alignment and Retention Time Correction of LC-MS Data in Proteomics”, University of Heidelberg, 2008.
R. Szeliski, Zabih, R., Scharstein, D., Veksler, O., Kolmogorov, V., Agarwala, A., Tappen, M., and Rother, C., “A comparative study of energy minimization methods for Markov random fields with smoothness-based priors”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, pp. 1068–1080, 2008.
R. Szeliski, Zabih, R., Scharstein, D., Veksler, O., Kolmogorov, V., Agarwala, A., Tappen, M., and Rother, C., “A comparative study of energy minimization methods for Markov random fields with smoothness-based priors”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, pp. 1068–1080, 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. Vlasenko and Schnörr, C., “Physically Consistent Variational Denoising of Image Fluid Flow Estimates”, in Pattern Recognition -- 30th DAGM Symposium, 2008, vol. 5096, p. 406--415.PDF icon Technical Report (1.6 MB)
A. Vlasenko and Schnörr, C., “Physically Consistent Variational Denoising of Image Fluid Flow Estimates”, in Pattern Recognition – 30th DAGM Symposium, 2008, vol. 5096, pp. 406–415.
O. Friedrich, Weber, C., Both, M., von Wegner, F., Chamberlain, J. S., Garbe, C. S., and Fink, R. H. A., “Sarcomere Structure and Motor-Protein Function in an Animal Model of Duchenne Muscular Dystrophy (mdx mouse)”, in 87th Annual Meeting of the German Physiological Society, 2008.
2007
T. Hara, VanInwegen, E., Wendelbo, J., Schimpf, U., Jähne, B., Frew, N. M., and Jähne, B., “Estimation of air-sea gas and heat fluxes from infrared imagery based on near surface turbulence models”, Transport at the Air Sea Interface --- Measurements, Models and Parameterizations. Springer-Verlag, 2007.
2006
F. Vogel, “Spectroscopic Techniques for Gas-Exchange Measurements”, Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2006.
2005
D. Banerjee, Schabel, S., Garbe, C. S., Schimpf, U., Jähne, B., and von Spiegel, W., “High resolution optical measurement techniques in paper drying”, Inpaper International - 9-10, vol. 4. p. 16--22, 2005.
2004
F. Vogel, “Visualisierung von Gasaustauschprozessen durch Lumineszenzspektroskopie mit Ruthenium als Phosphoreszenzstoff”. 2004.
2003
S. Hader and Hamprecht, F. A., “Efficient Density Clustering”, Between Data Science and Applied Data Analysis. Springer, pp. 39-48, 2003.
H. Eisele and Hamprecht, F. A., “A new approach for defect detection in X-ray CT images”, Pattern Recognition, vol. 2449. Springer, pp. 345-352, 2003.PDF icon Technical Report (398.88 KB)
2002
F. A. Hamprecht, Thiel, W., and van Gunsteren, W. F., “Chemical library subset selection algorithms: a unified derivation using spatial statistics”, Journal of Chemical Information and Computer Sciences, vol. 42, pp. 414-428, 2002.
A. Bruhn, Weickert, J., and Schnörr, C., “Combining the Advantages of Local and Global Optic Flow Methods”, in Pattern Recognition, Proc. 24th DAGM Symposium, Zürich, Switzerland, 2002, vol. 2449, pp. 454–462.
H. Spies and Garbe, C. S., “Dense parameter fields from total least squares”, in Proceedings of the 24th DAGM Symposium on Pattern Recognition, 2002, vol. LNCS 2449, p. 379--386.
A. Bruhn, Jakob, T., Fischer, M., Kohlberger, T., Weickert, J., Brüning, U., and Schnörr, C., “Designing 3–D Nonlinear Diffusion Filters for High Performance Cluster Computing”, in Pattern Recognition, Proc. 24th DAGM Symposium, Zürich, Switzerland, 2002, vol. 2449, pp. 290–297.
C. S. Garbe, Spies, H., and Jähne, B., “Mixed OLS-TLS for the estimation of dynamic processes with a linear source term”, in Proceedings of the 24th DAGM Symposium on Pattern Recognition, 2002, vol. 2449, p. 463--471.
P. J. Gee, Hamprecht, F. A., Schuler, L. D., van Gunsteren, W. F., Duchardt, E., Schwalbe, H., Albert, M., and Seebach, D., “A molecular dynamics simulation study of the conformational preferences of oligo-(3- hydroxyalcanoic acids) in chloroform solution”, Helv. Chim. Acta, vol. 85, pp. 618-632, 2002.
D. Cremers and Schnörr, C., “Motion Competition: Variational Integration of Motion Segmentation and Shape Regularization”, in Pattern Recognition, Proc. 24th DAGM Symposium, Zürich, Switzerland, 2002, vol. 2449, pp. 472–480.
J. Keuchel, Schnörr, C., Schellewald, C., and Cremers, D., “Unsupervised Image Partitioning with Semidefinite Programming”, in Pattern Recognition, Proc. 24th DAGM Symposium, Zürich, Switzerland, 2002, vol. 2449, pp. 141–149.
2001
F. A. Hamprecht, Achleitner, U., Krismer, A. C., Lindner, K. H., Wenzel, V., Strohmenger, H. - U., Thiel, W., and van Gunsteren, W. F., “Fibrillation power: An alternative method of ECG spectral analysis for prediction of countershock success in a porcine model of ventricular fibrillation”, Resuscitation, vol. 50, pp. 287-296, 2001.
F. A. Hamprecht, Peter, C., Daura, X., Thiel, W., and van Gunsteren, W. F., “A strategy for analysis of (molecular) equilibrium simulations: configuration space density estimation, clustering and visualization”, Journal of Chemical Physics, vol. 114, pp. 2079-2089, 2001.

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