Publications

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Haußecker, H and Jähne, B (2000). Radiation and illumination. Computer Vision and Applications - A Guide for Students and Practitioners. Academic Press. 11--52
Erz, M and Jähne, B (2009). Radiometric and spectrometric calibrations, and distance noise measurement of TOF cameras. 3rd Workshop on Dynamic 3-D Imaging. Springer. 5742 28--41
Gröning, (2003). Radiometrische Kalibrierung und Charakterisierung von CCD- uund CMOS-Bildsensoren und Monokulares 3D-Tracking in Echtzeit. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/3589
Haußecker, H, Jähne, B, Geißler, P and Haußecker, H (1999). Radiometry of imaging. Handbook of Computer Vision and Applications. Academic Press. 1: Sensors and Imaging 103--135
Haußecker, H and Jähne, B (2000). Radiometry of imaging. Computer Vision and Applications - A Guide for Students and Practitioners. Academic Press. 85--109
Massiceti, D, Krull, A, Brachmann, E, Rother, C and Torr, P H S (2017). Random Forests versus Neural Networks − What's best for camera location
Eigenstetter, A, Takami, M and Ommer, B (2014). Randomized Max-Margin Compositions for Visual Recognition. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. IEEE. 3590--3597PDF icon Technical Report (8.01 MB)
Spies, H, Jähne, B and Barron, J L (2002). Range flow estimation.. Computer Vision and Image Understanding. 85 209--231
Schmidt, M, Jehle, M and Jähne, B (2008). Range flow estimation based on photonic mixing device data. Int. J. Intelligent Systems Technologies and Applications. 5 380--392
Schmidt, M, Jehle, M and Jähne, B (2007). Range flow estimation based on photonic mixing device data. Proc.\ Dyn3D Workshop, Heidelberg, Sept. 11, 2007. ZESS, Univ.\ Siegen
Weickert, J and Schnörr, C (1999). Räumlich–zeitliche Berechnung des optischen Flusses mit nichtlinearen flussabhängigen Glattheitstermen. Mustererkennung 1999. Springer. 317–324
Strzodka, R and Garbe, C S (2004). Real-time motion estimation and visualization on graphics cards. Proceedings IEEE Visualization 2004. 545--552
Bruhn, A, Weickert, J, Feddern, C, Kohlberger, T and Schnörr, C (2003). Real-Time Optic Flow Computation with Variational Methods. Proc. Computer Analysis of Images and Patterns (CAIP'03). Springer. 2756 222-229
Hosseini Jafari, O and Yang, M Ying (2016). Real-time RGB-D based template matching pedestrian detection. Proceedings - IEEE International Conference on Robotics and Automation. 2016-June 5520–5527
Wiehler, K, Grigat, R –R, Heers, J, Schnörr, C and Stiehl, H –S (1998). Real–Time Adaptive Smoothing with a 1D Nonlinear Relaxation Network in Analogue VLSI Technology. Mustererkennung 1998. Springer, Heidelberg
Yarlagadda, P, Monroy, A, Carque, B and Ommer, B (2010). Recognition and Analysis of Objects in Medieval Images. Proceedins of the Aian Conference on Computer Vision, Workshop on e-Heritage. Springer. 296--305PDF icon Technical Report (2.76 MB)
Lang, S and Ommer, B (2018). Reconstructing Histories: Analyzing Exhibition Photographs with Computational Methods. Arts, Computational Aesthetics. 7, 64PDF icon arts-07-00064.pdf (4.6 MB)
Wanner, S and Goldlücke, B (2013). Reconstructing Reflective and Transparent Surfaces from Epipolar Plane Images. Pattern Recognition. Springer. 1--10
Monroy, A, Carque, B and Ommer, B (2011). Reconstructing the Drawing Process of Reproductions from Medieval Images. Proceedings of the International Conference on Image Processing. IEEE. 2974--2977. https://hciweb.iwr.uni-heidelberg.de/compvis/research/manesse/PDF icon Technical Report (2.43 MB)
Grützmann, (2009). Reconstruction of Moving Surfaces of Revolution from Sparse 3-D Measurements using a Stereo Camera and Structured Light. IWR, Fakultät für Mathematik und Informatik, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/10162
Gehler, P Vincent, Rother, C, Kiefel, M, Zhang, L and Schölkopf, B (2011). Recovering intrinsic images with a global sparsity prior on reflectance. Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011
Lang, S and Ommer, B (2018). Reflecting on How Artworks Are Processed and Analyzed by Computer Vision. European Conference on Computer Vision (ECCV - VISART). Springer
Nair, R, Fitzgibbon, A, Kondermann, D and Rother, C (2015). Reflection modeling for passive stereo. Proceedings of the IEEE International Conference on Computer Vision. 2015 Inter 2291–2299
Esparza, J, Vepa, L, Helmle, M and Jähne, B (2014). Registration of a multi-camera system with a 3D laser range finder. 9th Workshop Driver Assistance Systems (FAS2014), 26.-28.03.2014, Walting. 37--46. http://www.uni-das.de/de/Veranstaltungen/fas2014.php
Jancsary, J, Nowozin, S, Sharp, T and Rother, C (2012). Regression Tree Fields An efficient, non-parametric approach to image labeling problems. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2376–2383
Jancsary, J, Nowozin, S, Sharp, T and Rother, C (2012). Regression Tree Fields An efficient, non-parametric approach to image labeling problems. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2376–2383
Spies, H, Jähne, B and Barron, J L (2000). Regularised range flow. European Conference on Computer Vision (ECCV). Springer. 2 785--799
Lellmann, J and Schnörr, C (2011). Regularizers for Vector-Valued Data and Labeling Problems in Image Processing. Control Systems and Computers. 2 43–54
Rubio, J C and Ommer, B (2015). Regularizing Max-Margin Exemplars by Reconstruction and Generative Models. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. IEEE. 4213--4221PDF icon Technical Report (2.8 MB)
Bhowmik, A, Gumhold, S, Rother, C and Brachmann, E (2020). Reinforced Feature Points: Optimizing Feature Detection and Description for a High-Level Task. CVPR 2020 (oral). http://arxiv.org/abs/1912.00623PDF icon PDF (2.74 MB)
Bhowmik, A, Gumhold, S, Rother, C and Brachmann, E (2019). Reinforced Feature Points: Optimizing Feature Detection and Description for a High-Level Task. http://arxiv.org/abs/1912.00623
Reinecke, H, Fantana, N L, Haußecker, H and Jähne, B (1997). Rekonstruktion von Schreiberkurven. Mustererkennung 1997. Springer. 527--536
von Schmude, N, Lothe, P and Jähne, B (2016). Relative Pose Estimation from Straight Lines using Parallel Line Clustering and its Application to Monocular Visual Odometry. Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
Garbe, C S and Jähne, B (2001). Reliable estimates of the sea surface heat flux from image sequences. Proceedings of the 23th DAGM Symposium on Pattern Recognition, München. Springer. 194--201
Köthe, (2008). Reliable Low-Level Image Analysis. Habilitation thesis. Department Informatik, University of Hamburg, HamburgPDF icon Technical Report (12.44 MB)

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