Publications

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Journal Article
P. Kohli, Nickisch, H., Rother, C., and Rhemann, C., User-centric learning and evaluation of interactive segmentation systems, International Journal of Computer Vision, vol. 100, pp. 261–274, 2012.
B. Michael Kelm, Kaster, F. O., Henning, A., Weber, M. - A., Bachert, P., Bösinger, P., Hamprecht, F. A., and Menze, B. H., Using Spatial Prior Knowledge in the Spectral Fitting of Magnetic Resonance Spectroscopic Images, NMR in Biomedicine, vol. 25(1), pp. 1-13, 2011.PDF icon Technical Report (1.94 MB)
F. Becker, Wieneke, B., Petra, S., Schröder, A., and Schnörr, C., Variational Adaptive Correlation Method for Flow Estimation, IEEE Transactions on Image Processing, vol. 21, 6, pp. 3053 - 3065, 2011.
F. Becker, Wieneke, B., Petra, S., Schröder, A., and Schnörr, C., Variational Adaptive Correlation Method for Flow Estimation, IEEE Transactions on Image Processing, vol. 21, pp. 3053 – 3065, 2012.
F. Becker, Wieneke, B., Petra, S., Schröder, A., and Schnörr, C., Variational Adaptive Correlation Method for Flow Estimation, IEEE Transactions on Image Processing, vol. 21, p. 3053 -- 3065, 2012.PDF icon Technical Report (18.81 MB)
P. Ruhnau, Gütter, C., Putze, T., and Schnörr, C., A variational approach for particle tracking velocimetry, Meas. Science and Techn., vol. 16, pp. 1449-1458, 2005.
C. Schnörr, Sprengel, R., and Neumann, B., A Variational Approach to the Design of Early Vision Algorithms, Computing Suppl., vol. 11, pp. 149-165, 1996.
P. Ruhnau, Stahl, A., and Schnörr, C., Variational Estimation of Experimental Fluid Flows with Physics-Based Spatio-Temporal Regularization, Measurement Science and Technology, vol. 18, pp. 755-763, 2007.
P. Ruhnau, Stahl, A., and Schnörr, C., Variational Estimation of Experimental Fluid Flows with Physics-Based Spatio-Temporal Regularization, Measurement Science and Technology, vol. 18, pp. 755-763, 2007.PDF icon Technical Report (842.06 KB)
D. Heitz, Mémin, E., and Schnörr, C., Variational fluid flow measurements from image sequences: synopsis and perspectives, Exp.~Fluids, vol. 48, pp. 369-393, 2010.PDF icon Technical Report (1.91 MB)
D. Heitz, Mémin, E., and Schnörr, C., Variational fluid flow measurements from image sequences: synopsis and perspectives, Exp. Fluids, vol. 48, pp. 369-393, 2010.
S. Wanner and Goldlücke, B., Variational light field analysis for disparity estimation and super-resolution, IEEE Trans. Pattern Analysis Machine Intelligence, vol. 36, p. 606--619, 2014.
A. Bruhn, Weickert, J., Feddern, C., Kohlberger, T., and Schnörr, C., Variational optic flow computation in real-time, IEEE Trans. Image Proc., vol. 14, pp. 608–615, 2005.
J. Weickert and Schnörr, C., Variational Optic Flow Computation with a Spatio-Temporal Smoothness Constraint, J. Math. Imaging and Vision, vol. 14, pp. 245–255, 2001.
P. Ruhnau, Kohlberger, T., Nobach, H., and Schnörr, C., Variational Optical Flow Estimation for Particle Image Velocimetry, Experiments in Fluids, vol. 38, pp. 21–32, 2005.
P. Ruhnau, Kohlberger, T., Nobach, H., and Schnörr, C., Variational Optical Flow Estimation for Particle Image Velocimetry, Experiments in Fluids, vol. 38, p. 21--32, 2005.PDF icon Technical Report (1.21 MB)
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, International Journal of Computer Vision, vol. 105, no. 3, p. 269--297, 2013.PDF icon Technical Report (15.4 MB)
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, International Journal of Computer Vision, vol. 105 (3), pp. 269-297, 2013.
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, International Journal of Computer Vision, vol. 105, pp. 269–297, 2013.
J. Kleesiek, Petersen, J., Döring, M., Maier-Hein, K., Köthe, U., Wick, W., Hamprecht, F. A., Bendszus, M., and Biller, A., Virtual Raters for Reproducible and Objective Assessments in Radiology, Nature Scientific Reports, vol. 6, 2016.PDF icon Technical Report (2.81 MB)
N. Gianniotis and Tiño, P., Visualization of Structured Data via Generative Probabilistic Modeling, Pattern Recognition, vol. 5400, pp. 118-137, 2009.
M. Pfannmöller, Flügge, H., Benner, G., Wacker, I., Sommer, C., Hanselmann, M., Schmale, S., Schmidt, H., Hamprecht, F. A., Rabe, T., Kowalsky, W., and Schröder, R., Visualizing a homogeneous blend in bulk heterojunction polymer solar cells by analytical electron microscopy, Nano Letters, vol. 11, pp. 3099-3107, 2011.
Q. Garrido, Damrich, S., Jäger, A., Cerletti, D., Claassen, M., Najman, L., and Hamprecht, F. A., Visualizing hierarchies in scRNA-seq data using a density tree-biased autoencoder, Bioinformatics, vol. 38 (Suppl 1), pp. i316-i324, 2022.
F. A. Hamprecht and Jähne, B., Vom Bild zur Information, Ruperto Carola -- Forschungsmagazin der Universität Heidelberg, vol. 03.2004, pp. 9-12, 2004.
D. Kiefhaber, Caulliez, G., Zappa, C. J., Schaper, J., and Jähne, B., Water wave measurement from stereo images of specular reflections, vol. 26, p. 115401, 2015.
M. Jäger, Knoll, C., and Hamprecht, F. A., Weakly Supervised Learning of a Classifier for Unusual Event Detection, IEEE Transactions on Image Processing, vol. 17, pp. 1700-1708, 2008.PDF icon Technical Report (295.32 KB)
B. Jähne, Köhler, H. - J., Rath, R., and Wierzimok, D., Wellenamplitudenmessungen mittels videometrischer Bildverarbeitung, Mitteilungsblatt der Bundesanstalt für Wasserbau, vol. 70, p. 27--62, 1993.
S. Meister, Izadi, S., Kohli, P., and M Hämmerle, M. \, When can we use KinectFusion for ground truth acquisition?, Proc Workshop on \ldots, pp. 3–8, 2012.
P. Márquez-Valle, Gil, D., Hernàndez-Sabaté, A., and Kondermann, D., When is a confidence measure good enough?, submitted to CVPR 2013, 2013.
B. Y. Renard, Kirchner, M., Monigatti, F., Ivanov, A. R., Rappsilber, J., Winter, D., Steen, J. A. J., Hamprecht, F. A., and Steen, H., When Less Can Yield More - Computational Preprocessing of MS/MS Spectra for Peptide Identification Preprocessing, Proteomics, vol. 9, pp. 4978-4984, 2009.PDF icon Technical Report (901.78 KB)
B. Jähne, When the invisible becomes visible, German research, Magazine of the German Research Foundation (DFG), p. 30--33, 1999.
E. - A. Horvát, Hanselmann, M., Hamprecht, F. A., and Zweig, K. A., You Are Who Knows You: Predicting Links Between Non-Members of Facebook, European Conference on Complex Systems. Proceedings, vol. 3, pp. 309-315, 2012.PDF icon Technical Report (1.92 MB)
B. Jähne, Zukunftsperspektiven der industriellen Bildverarbeitung - Was kann die akademische Forschung beitragen?, Optik & Photonik, vol. 3, pp. 28-33, 2008.
Masters Thesis
A. Horn, IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2011.
D. Kimmich, IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2011.

Pages