All Publications

2010

Rother, C, Kohli, P, Feng, W and Jia, J (2010). Minimizing sparse higher order energy functions of discrete variables. 1382–1389
Nickisch, H, Rother, C, Kohli, P and Rhemann, C (2010). Learning an Interactive Segmentation System - Supplemental Material
Chellappa, R and Machinery., Afor Comput (2010). Proceedings - 7th Indian Conference on Computer Vision, Graphics and Image Processing, ICVGIP 2010. ACM International Conference Proceeding Series. ACM
Lempitsky, V, Rother, C, Roth, S and Blake, A (2010). Fusion moves for markov random field optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence. 32 1392–1405
Lempitsky, V, Rother, C, Roth, S and Blake, A (2010). Fusion moves for markov random field optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence. 32 1392–1405
Mansfield, A, Gehler, P, Van Gool, L and Rother, C (2010). Scene carving: Scene consistent image retargeting. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6311 LNCS 143–156. www.fujifilm.com/products/3d/camera/finepix_
Glocker, B, T. Heibel, H, Navab, N, Kohli, P and Rother, C (2010). TriangleFlow: Optical flow with triangulation-based higher-order likelihoods. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6313 LNCS 272–285. http://vision.middlebury.edu/flow/
Vicente, S, Kolmogorov, V and Rother, C (2010). Cosegmentation revisited: Models and optimization. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6312 LNCS 465–479
Ding, L and Yilmaz, A (2010). Interactive image segmentation using probabilistic hypergraphs. Pattern Recognition. 43 1863–1873. http://www.research.microsoft.com/vision/cambridge
Bleyer, M, Rother, C and Kohli, P (2010). Surface stereo with soft segmentation. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 1570–1577
Rhemann, C, Rother, C, Kohli, P and Gelautz, M (2010). A spatially varying PSF-based prior for alpha matting. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2149–2156
Gulshan, V, Rother, C, Criminisi, A, Blake, A and Zisserman, A (2010). Geodesic star convexity for interactive image segmentation. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 3129–3136
Bergtholdt, M, Kappes, J H, Schmidt, S and Schnörr, C (2010). A Study of Parts-Based Object Class Detection Using Complete Graphs. Int. J. Comp. Vision. 87 93-117. http://www.springerlink.com/openurl.asp?genre=article&id=doi:10.1007/s11263-009-0209-1
Breitenreicher, D and Schnörr, C (2010). Robust 3D object registration without explicit correspondence using geometric integration. Machine Vision and Applications. 21 601-611. http://www.springerlink.com/content/g20710062l014241/
Heitz, D, Mémin, E and Schnörr, C (2010). Variational fluid flow measurements from image sequences: synopsis and perspectives. Exp. Fluids. 48 369-393
Kappes, J H, Schmidt, S and Schnörr, C (2010). MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation. European Conference on Computer Vision (ECCV). Springer Berlin / Heidelberg. 6313 735–747
Lellmann, J, Breitenreicher, D and Schnörr, C (2010). Fast and Exact Primal-Dual Iterations for Variational Problems in Computer Vision. European Conference on Computer Vision (ECCV). Springer Berlin / Heidelberg. 6312 494–505
Lellmann, J and Schnörr, C (2010). Continuous Multiclass Labeling Approaches And Algorithms. Univ. of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/10460/
Vlasenko, A and Schnörr, C (2010). Physically Consistent and Efficient Variational Denoising of Image Fluid Flow Estimates. IEEE Trans. Image Proc. 19 586-595

2009

Ommer, B, Mader, T and Buhmann, J M (2009). Seeing the Objects Behind the Dots: Recognition in Videos from a Moving Camera. International Journal of Computer Vision. Springer. 83 57--71PDF icon Technical Report (9.61 MB)
Ommer, B and Malik, J (2009). Multi-scale Object Detection by Clustering Lines. Proceedings of the IEEE International Conference on Computer Vision. IEEE. 484--491PDF icon Technical Report (3.18 MB)
Yarlagadda, P, Monroy, A, Carque, B and Ommer, B (2009). Towards a Computer-based Understanding of Medieval Images. Scientific Computing & Cultural Heritage. Springer. 89--97. http://link.springer.com/chapter/10.1007%2F978-3-642-28021-4_10#page-1
Keränen, S V E, DePace, A, Hendriks, C L Luengo, Fowlkes, C, Arbelaez, P, Ommer, B, Brox, T, Henriquez, C, Wunderlich, Z, Eckenrode, K, Fischer, B, Hammonds, A and Celniker, S E (2009). Computational Analysis of Quantitative Changes in Gene Expression and Embryo Morphology between Species. Evolution-The Molecular Landscape
Andres, B, Köthe, U, Bonea, A, Nadler, B and Hamprecht, F A (2009). Quantitative Assessment of Image Segmentation Quality by Random Walk Relaxation Times. Pattern Recognition. 31st DAGM Symposium, Jena, Germany, September 9-11, 2009. Proceedings. Springer. 5748 502-511PDF icon Technical Report (3.08 MB)
Bähnisch, C, Stelldinger, P and Köthe, U (2009). Fast and Accurate 3D Edge Detection for Surface Reconstruction. Pattern Recognition. Springer. 5748 111-120
Frank, M, Plaue, M and Hamprecht, F A (2009). Denoising of Continuous-Wave Time-Of-Flight Depth Images Using Confidence Measures. Optical Engineering. 48, 077003PDF icon Technical Report (2.5 MB)
Görlitz, L, Hamprecht, F A and Staudacher, M (2009). Allocation of particles to development processes. PatentPDF icon Technical Report (406.7 KB)
Görlitz, L, Menze, B H, Kelm, B Michael and Hamprecht, F A (2009). Processing Spectral Data. Surface and Interface Analysis. 41 636-644PDF icon Technical Report (4.17 MB)
Greis, J (2009). Semi-Automatic Analysis Of High-Information-Content Neurobiological Image Data. University of Heidelberg
Hanselmann, M, Köthe, U, Kirchner, M, Renard, B Y, Amstalden, E R, Glunde, K, Heeren, R M A and Hamprecht, F A (2009). Towards Digital Staining using Imaging Mass Spectrometry and Random Forests. Journal of Proteome Research. 8 3558-3567PDF icon Technical Report (1.47 MB)
Hanselmann, M, Köthe, U, Renard, B Y, Kirchner, M, Heeren, R M A and Hamprecht, F A (2009). Multivariate Watershed Segmentation of Compositional Data. Proceedings of the 15th International Conference on Discrete Geometry for Computer Imagery (DGCI), in press. Springer. 5810 180-192PDF icon Technical Report (1.25 MB)
Hayn, M, Beirle, S, Hamprecht, F A, Platt, U, Menze, B H and Wagner, T (2009). Analysing spatio-temporal patterns of the global NO2-distribution retrieved frome GOME satellite observations using a generalized additive model. Atmospheric Chemistry and Physics. 9 9367-9398PDF icon Technical Report (2.52 MB)
Jäger, M, Kiel, A, Herten, D - P and Hamprecht, F A (2009). Analysis of Single-Molecule Fluorescence Spectroscopic Data with a Markov Modulated Poisson Process. ChemPhysChem. 10:14 2486-2495
Kassemeyer, S (2009). Quantification Of Tumour Angiogenesis Using Pattern Recognition. University of Heidelberg
Kaster, F O, Kelm, B Michael, Zechmann, C M, Weber, M - A, Hamprecht, F A and Nix, O (2009). Classification of Spectroscopic Images in the DIROlab Environment. World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany. Springer. 25/V 252--255PDF icon Technical Report (145.73 KB)
Kelm, B Michael, Menze, B H, Nix, O, Zechmann, C M and Hamprecht, F A (2009). Estimating Kinetic Parameter Maps from Dynamic Contrast-Enhanced MRI using Spatial Prior Knowledge. IEEE Transaction on Medical Imaging. 28:10 1534-1547PDF icon Technical Report (419.8 KB)
Meine, H, Köthe, U and Stelldinger, P (2009). Pixel Approximation Errors in Common Watershed Algorithms. Discrete Geometry for Computer Imagery. Springer. 5810 193-202PDF icon Technical Report (6.5 MB)
Menze, B H, Kelm, B Michael, Masuch, R, Himmelreich, U, Bachert, P, Petrich, W and Hamprecht, F A (2009). A Comparison of Random Forest and its Gini Importance with Standard Chemometric Methods for the Feature Selection and Classification of Spectral Data. BMC Bioinformatics. 10:213PDF icon Technical Report (675 KB)
Ozlu, N, Monigatti, F, Renard, B Y, Field, C M, Steen, H, Mitchison, T J and Steen, J J (2009). Binding partner switching on microtubules and aurora-B in the mitosis to cytokinesis transition. Molecular & Cellular Proteomics
Renard, B Y, Kirchner, M, Monigatti, F, Ivanov, A R, Rappsilber, J, Winter, D, Steen, J A J, Hamprecht, F A and Steen, H (2009). When Less Can Yield More - Computational Preprocessing of MS/MS Spectra for Peptide Identification Preprocessing. Proteomics. 9 4978-4984PDF icon Technical Report (901.78 KB)

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