Publications

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Hornáček, M, Besse, F, Kautz, J, Fitzgibbon, A and Rother, C (2014). Highly overparameterized optical flow using PatchMatch belief propagation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8691 LNCS 220–234
Netzsch, T and Jähne, B (1995). A high-performance system for 3-dimensional particle tracking velocimetry in turbulent flow research using image sequences. Proc. ISPRS Intercommission workshop From Pixels to Sequences, Zürich, March 22-24. Risc Books. 30 Part 5W1 202--207
Kräuter, C, Trofimova, D, Nagel, L and Jähne, B (2014). High-resolution 2-D fluorescence imaging of gas transfer at a free water surface. Ocean Science Meeting, 23--28. 02. 2014, Honolulu Hawaii
Kiefhaber, D, Reith, S, Rocholz, R and Jähne, B (2014). High-speed imaging of short wind waves by shape from refraction. J. Europ. Opt. Soc. Rap. Public. 9 14015
Horn, J (2013). Hochaufgelöste Optische Wellenhöhenmessung Am Aeolotron Mit Laser-Induzierter Fluoreszenz. Institut für Umwelphysik, Univeristät Heidelberg, Germany
Warken, P (2010). Hochauflösende Lif-Methode Zur Messung Von Sauerstoffkonzentrationsprofilen In Der Wasserseitigen Grenzschicht. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Fahle, P (2013). Hochauflösende Messung Der Raumzeitlichen Variation Der Neigung Winderzeugter Wasserwellen. Institut für Umwelphysik, Univeristät Heidelberg, Germany
Friedl, F, Herzog, A G, Warken, P and Jähne, B (2011). Hochauflösende raumzeitliche Messung von flüssigkeitsseitigen Konzentrationsfeldern an der wind- und wellenbewegten Wasseroberfläche. DPG Frühjahrstagung Dresden. http://www.dpg-verhandlungen.de/year/2011/conference/dresden/part/up/session/5/contribution/3
Franke, R (2012). Hochintegriertes Kamerasystem für die Multifrequenz-Lumineszenzabklingzeitbildgewinnung. IWR, Fakultät für Mathematik und Informatik, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/13464
Franke, R (2012). Hochintegriertes Kamerasystem für die Multifrequenz-Lumineszenzabklingzeitbildgewinnung. IWR, Fakultät für Mathematik und Informatik, Univ. Heidelberg. Dissertation
Haußecker, H, Shear, R, Melville, W K and Jähne, B (1995). Horizontal and vertical spatial structures of turbulence beneath short wind waves. IAPSO Proceedings, XXI General Assembly, Honolulu, Hawai, August 1995, PS-10 Spatial Structure of Short Ocean Waves. 384
Restle, J (2001). Horizontal scannendes Wei\DFlicht-Interferometer. Robert Bosch GmbH
Donath, A and Kondermann, D (2013). How Good is Crowdsourcing for Optical Flow Ground Truth Generation?. submitted to CVPR
Andres, B, Köthe, U, Kröger, T and Hamprecht, F A (2010). How to Extract the Geometry and Topology from Very Large 3D Segmentations. ArXiv e-prints. http://arxiv.org/abs/1009.6215PDF icon Technical Report (1.44 MB)
Schmidt, M (2008). How to perform camera measurements according to the EMVA 1288 Standard.
Jähne, B, Jähne, B and Haußecker, H (1999). Hyperspectral and color imaging. Handbook of Computer Vision and Applications. Volume I: Sensors and Imaging. Academic Press. 309--320
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Kleesiek, J, Biller, A, Urban, G, Köthe, U, Bendszus, M and Hamprecht, F A (2014). ilastik for Multi-modal Brain Tumor Segmentation. MICCAI BraTS (Brain Tumor Segmentation) Challenge. Proceedings, 3rdplace. 12-17PDF icon Technical Report (405.91 KB)
Sommer, C, Straehle, C N, Köthe, U and Hamprecht, F A (2011). ilastik: Interactive Learning and Segmentation Toolkit. Eighth IEEE International Symposium on Biomedical Imaging (ISBI 2011).Proceedings. 230-233
Berg, S, Kutra, D, Kroeger, T, Straehle, C N, Kausler, B X, Haubold, C, Schiegg, M, Ales, J, Beier, T, Rudy, M, Eren, K, Cervantes, J I, Xu, B, Beuttenmüller, F, Wolny, A, Zhang, C, Köthe, U, Hamprecht, F A and Kreshuk, A (2019). ilastik: interactive machine learning for (bio)image analysis. Nature Methods. 16 1226-1232
Haußecker, H, Jähne, B, Geißler, P and Haußecker, H (1999). Illumination sources and techniques. Handbook of Computer Vision and Applications. Academic Press. 1: Sensors and Imaging 137--162
Kaster, F O (2011). Image Analysis for the Life Sciences - Computer-assisted Tumor Diagnostics and Digital Embryomics. University of Heidelberg
Schellewald, C, Keuchel, J and Schnörr, C (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, INRIA, Sophia Antipolis, France. 2134 267–282
Hühnerbein, R, Savarino, F, Aström, F and Schnörr, C (2018). Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment. SIAM Journal on Imaging Sciences. 11 1317-1362PDF icon Technical Report (2.62 MB)
Hühnerbein, R, Savarino, F, Aström, F and Schnörr, C (2018). Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment. SIAM J. Imaging Science. 11 1317–1362. https://epubs.siam.org/doi/abs/10.1137/17M1150669
Hühnerbein, R, Savarino, F, Aström, F and Schnörr, C (2017). Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment. http://arxiv.org/abs/1710.01493
Aström, F, Petra, S, Schmitzer, B and Schnörr, C (2017). Image Labeling by Assignment. J. Math. Imag. Vision. 58 211–238. Papers/Astroem2017.pdf
Aström, F, Petra, S, Schmitzer, B and Schnörr, C (2016). Image Labeling by Assignment. http://arxiv.org/abs/1603.05285
Schleicher, J (2011). Image Processing For Super-Resolution Localization Microscopy Utilizing An Fpga Accelerator. University of Heidelberg
Zisler, M, Aström, F, Petra, S and Schnörr, C (2017). Image Reconstruction by Multilabel Propagation. Proc. SSVM. Springer. 10302
Lempitsky, V, Blake, A and Rother, C (2008). Image segmentation by branch-and-mincut. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5305 LNCS 15–29
Lempitsky, V, Blake, A and Rother, C (2008). Image segmentation by branch-and-mincut. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5305 LNCS 15–29
Lempitsky, V, Kohli, P, Rother, C and Sharp, T (2009). Image segmentation with a bounding box prior. Proceedings of the IEEE International Conference on Computer Vision. 277–284
Geese, M (2013). Image Sensor Nonuniformity Correction by a Scene-Based Maximum Likelihood Approach. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/14391
Geese, M (2013). Image Sensor Nonuniformity Correction by a Scene-Based Maximum Likelihood Approach. IWR, Univ. Heidelberg. Dissertation
Jähne, (2003). Image sequence analysis in environmental and live sciences. Proceedings of the 25th DAGM Symposium on Pattern Recognition. Springer. 2781 608--617

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