Publications

Berthe, A, Kondermann, D, Jähne, B and Ketzscher, U (2009). The wall PIV measurement technique for near wall flow fields in biofliud mechanics. Imaging Measurement Methods for Flow Analysis, Results of the DFG Priority Programme 1147 Imaging Measurement Methods for Flow Analysis 2003-2009. Springer. 106 11--20

Berthe, A, Kondermann, D, Christensen, C, Goubergrits, L, Garbe, C S, Affeld, K and Kertzscher, U (2010). Three-dimensional, three-component wall-PIV. Exp. Fluids. 48 online

Beringer, O (1998). Ein Messsystem Zur Untersuchung Von Sedimentverlagerungen Und Durchmischungsprozessen Mittels Digitaler Bildfolgenanalyse. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg

Bergtholdt, M, Cremers, D and Schnörr, C (2005). Variational Segmentation with Shape Priors. Handbook of Mathematical Models in Computer Vision. Springer. 147-160

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

Bergtholdt, M, Kappes, J H and Schnörr, C (2006). Learning of Graphical Models and Efficient Inference for Object Class Recognition. Proc. DAGM 2006. Springer. 375-388 375-388

Bergtholdt, M and Schnörr, C (2005). Shape Priors and Online Appearance Learning for Variational Segmentation and Object Recognition in Static Scenes. Pattern Recognition, Proc. 27th DAGM Symposium. Springer. 3663 342–350

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

Technical Report (2.18 MB)

Berger, J and Schnörr, C (2016). Joint Recursive Monocular Filtering of Camera Motion and Disparity Map. 38th German Conference on Pattern Recognition. Springer, Hannover. https://arxiv.org/abs/1606.02092

Technical Report (2.34 MB)

Berger, J, Lenzen, F, Becker, F, Neufeld, A and Schnörr, C (2017). {Second-Order Recursive Filtering on the Rigid-Motion Lie Group SE(3) Based on Nonlinear Observations. J. Math. Imag. Vision. 58 102–129

Berger, J and Schnörr, C (2016). Joint Recursive Monocular Filtering of Camera Motion and Disparity Map. 38th German Conference on Pattern Recognition

Berger, J, Neufeld, A, Becker, F, Lenzen, F and Schnörr, C (2015). Second Order Minimum Energy Filtering on SE(3) with Nonlinear Measurement Equations. Scale Space and Variational Methods in Computer Vision (SSVM 2015)

Berger, J, Lenzen, F, Becker, F, Neufeld, A and Schnörr, C (2015). Second-Order Recursive Filtering on the Rigid-Motion Lie Group SE(3) Based on Nonlinear Observations. http://arxiv.org/abs/1507.06810

Berger, J, Neufeld, A, Becker, F, Lenzen, F and Schnörr, C (2015). Second Order Minimum Energy Filtering on SE(3) with Nonlinear Measurement Equations. Scale Space and Variational Methods in Computer Vision (SSVM 2015). Springer International Publishing. http://dx.doi.org/10.1007/978-3-319-18461-6_32

Technical Report (364.01 KB)

Berger, J, Lenzen, F, Becker, F, Neufeld, A and Schnörr, C (2015). Second-Order Recursive Filtering on the Rigid-Motion Lie Group SE(3) Based on Nonlinear Observations. http://arxiv.org/abs/1507.06810

Technical Report (4.42 MB)

Berger, K, Meister, S, Nair, R and Kondermann, D (2013). A State of the Art Report on Kinect Sensor Setups in Computer Vision. Time-of-Flight and Depth Imaging. Sensors, Algorithms, and Applications. Springer. 8200 257-272

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

Beranek, R (1996). Vermessung Von Blickpunkten Durch Automatische Bildanalyse Für Ergonomische Fragestellungen Bei Der Fahrzeugkonstruktion. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg

Bentele, M (1998). Zeitliche Rekonstruktion Und Visualisierung Dynamischer Prozesse. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg

Bengio, Y, Deleu, T, Rahaman, N, Ke, R, Lachapelle, S, Bilaniuk, O, Goyal, A and Pal, C (2019). A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms. arXiv preprint arXiv:1901.10912

Technical Report (871.59 KB)

Bendinger, A L, Debus, C, Glowa, C, Karger, C P, Peter, J and Storath, M (2019). Bolus arrival time estimation in dynamic contrast-enhanced magnetic resonance imaging of small animals based on spline models, in press. Physics in Medicine and Biology. 64

Bellagente, M, Haußmann, M, Luchmann, M and Plehn, T (2021). Understanding Event-Generation Networks via Uncertainties. arXiv preprint. https://arxiv.org/abs/2104.04543v1

Bell, P and Ommer, B (2016). Digital Connoisseur? How Computer Vision Supports Art History. Connoisseurship nel XXI secolo. Approcci, Limiti, Prospettive, A. Aggujaro & S. Albl (ed.). Artemide, Rome

Bell, P and Ommer, B (2018). Computer Vision und Kunstgeschichte — Dialog zweier Bildwissenschaften. Computing Art Reader: Einführung in die digitale Kunstgeschichte, P. Kuroczyński et al. (ed.)

413-17-83318-2-10-20181210.pdf (2.98 MB)

Bell, P and Ommer, B (2015). Training Argus. Kunstchronik. Monatsschrift für Kunstwissenschaft, Museumswesen und Denkmalpflege. Zentralinstitut für Kunstgeschichte. 68 414--420