Publications

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2008
M. Schmidt, Spatiotemporal Analysis of Range Imagery. IWR, Fakultät für Physik und Astronomie, University of Heidelberg, 2008.
R. Rocholz, Spatiotemporal Measurement of Short Wind-Driven Water Waves. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2008.
M. Jäger, Humbert, S., and Hamprecht, F. A., Sputter Tracking for the Automatic Monitoring of Industrial Laser Welding Processes, IEEE Transactions on Industrial Electronics, vol. 55, pp. 2177-2184, 2008.PDF icon Technical Report (1.83 MB)
C. Kondermann, Mester, R., and Garbe, C. S., A statistical confidence measure for optical flows, in Proceedings of the ECCV, 2008, vol. 5304, p. 290--301.
2009
B. Ommer, Mader, T., and Buhmann, J. M., Seeing the Objects Behind the Dots: Recognition in Videos from a Moving Camera, International Journal of Computer Vision, vol. 83, p. 57--71, 2009.PDF icon Technical Report (9.61 MB)
M. Staudacher, Hamprecht, F. A., and Görlitz, L., Self Adjustment of Scanning Electron Microscopes / Selbstadaptivität von Rasterelektronenmikroskopen, Patent, Patent Number WO2009062781A1, 2009.PDF icon Technical Report (46.64 KB)
J. Greis, Semi-automatic analysis of high-information-content neurobiological image data, University of Heidelberg, 2009.
T. Kumpf, Sichtfelddesign mittels Freiformspiegel für katadioptrische Systeme, IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2009.
C. S. Garbe, Kondermann, D., Jehle, M., and Jähne, B., Spatiotemporal image analysis for flow measurements, Imaging Measurement Methods for Flow Analysis, Results of the DFG Priority Programme 1147 Imaging Measurement Methods for Flow Analysis 2003-2009, vol. 106. Springer, p. 289--305, 2009.
F. Lauer and Schnörr, C., Spectral Clustering of Linear Subspaces for Motion Segmentation, in Proceedings of the IEEE Conference on Computer Vision (ICCV 09) Kyoto, Japan, in press, 2009, pp. 678-685.
F. Lauer and Schnörr, C., Spectral Clustering of Linear Subspaces for Motion Segmentation, in Proc.~IEEE Int.~Conf.~Computer Vision (ICCV'09), 2009.PDF icon Technical Report (1.12 MB)
F. Lauer and Schnörr, C., Spectral Clustering of Linear Subspaces for Motion Segmentation, in Proc. IEEE Int. Conf. Computer Vision (ICCV'09), Kyoto, Japan, 2009.
M. Bleyer, Gelautz, M., Rother, C., and Rhemann, C., A stereo approach that handles the matting problem via imagewarping, in 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009, 2009, vol. 2009 IEEE, pp. 501–508.
D. Singaraju, Rother, C., and Rhemann, C., Supplementary material for New Appearance Models for Image Matting, 2009.
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.
R. Weber, Setup of a Laser Slope Gauge for the Measurement of Wave Slope Distributions at the Small Circular Wind Wave Facility, Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2010.
A. G. Herzog, Friedl, F., and Jähne, B., Simultaneous high-resolution LIF measurements of dissolved gas concentration fields and measurements of wave slope at a wavy free water surface with wind-induced turbulence, in 15h Int. Symp on Appl. Laser Techniques to Fluid Mechanics, Lisbon, Portugal, July 05--08, 2010, 2010.
M. Atif, Zimmermann, K., and Jähne, B., A space-variant (3D) image simulation tool for computational cameras, in International Conference on Computational Photography (ICCP) 2010, 2010.
C. Rhemann, Rother, C., Kohli, P., and Gelautz, M., A spatially varying PSF-based prior for alpha matting, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010, pp. 2149–2156.
A. G. Herzog, Friedl, F., and Jähne, B., Spatio-temporal fluctuations of water-sided gas concentration fields under wind-induced turbulence, in 6th Int. Symp. Gas Transfer at Water Surfaces, Kyoto, May 17--21, 2010, 2010.
R. Rocholz and Jähne, B., Spatio-temporal measurements of short wind water waves, in EGU General Assembly 2010, Symposium AS2.2, 2010, pp. EGU2010-5509.
F. Rathke, Hansen, K., Brefeld, U., and Müller, K. - R., StructRank: A new approach for ligand-based virtual screening, J. Chem. Inf. Model., vol. 51, pp. 83–92, 2010.
M. Bergtholdt, Kappes, J. H., Schmidt, S., and Schnörr, C., A Study of Parts-Based Object Class Detection Using Complete Graphs, Int.~J.~Comp.~Vision, vol. 87, pp. 93-117, 2010.PDF icon Technical Report (2.18 MB)
M. Bergtholdt, Kappes, J. H., Schmidt, S., and Schnörr, C., A Study of Parts-Based Object Class Detection Using Complete Graphs, Int. J. Comp. Vision, vol. 87, pp. 93-117, 2010.
S. Meister, A Study on Ground Truth Generation for Optical Flow, University of Heidelberg, 2010.
M. Bleyer, Rother, C., and Kohli, P., Surface stereo with soft segmentation, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010, pp. 1570–1577.
2011
M. Hanselmann, Voss, B., Renard, B. Y., Lindner, M., Köthe, U., Kirchner, M., and Hamprecht, F. A., SIMA: Simultaneous Multiple Alignment of LC/MS Peak Lists, Bioinformatics, vol. 27 (7), pp. 987-993, 2011.PDF icon Technical Report (2.2 MB)
C. Rother, Sparse Higher Order Functions of Discrete Variables–-Representation and Optimization, research.microsoft.com, vol. 45, 2011.
D. Breitenreicher, Lellmann, J., and Schnörr, C., Sparse Template-Based Variational Image Segmentation, Advances in Adaptive Data Analysis, vol. 3, pp. 149-166, 2011.PDF icon Technical Report (866.28 KB)
D. Breitenreicher, Lellmann, J., and Schnörr, C., Sparse Template-Based Variational Image Segmentation, Advances in Adaptive Data Analysis, vol. 3, pp. 149-166, 2011.
X. Lou and Hamprecht, F. A., Structured Learning for Cell Tracking, in NIPS 2011. Proceedings, 2011, pp. 1296-1304.PDF icon Technical Report (1.41 MB)
B. Savchynskyy, Kappes, J. H., Schmidt, S., and Schnörr, C., 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, pp. 1817 - 1823, 2011.
B. Savchynskyy, Kappes, J. H., Schmidt, S., and Schnörr, C., A Study of Nesterov's Scheme for Lagrangian Decomposition and MAP Labeling, in IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2011.PDF icon Technical Report (408.99 KB)
B. Savchynskyy, Kappes, J. H., Schmidt, S., and Schnörr, C., A Study of Nesterov's Scheme for Lagrangian Decomposition and MAP Labeling, in IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2011.
S. Nowozin and Sharp, T., Supplementary Material : Decision Tree Fields, Iccv, 2011.

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