Export 1514 results:
Author [ Title(Asc)] Type Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
Renard, B Y (2010). Robust Methods for the Proteomic Data Analysis Pipeline. University of Heidelberg
Breitenreicher, D and Schnörr, C (2010). Robust 3D object registration without explicit correspondence using geometric integration. Machine Vision and Applications. 21 601-611. icon Technical Report (1.65 MB)
Álvarez, J M, Gevers, T, Diego, F and López, A M (2012). Road Geometry Classification by Adaptive Shape Models. IEEE Transactions on Intelligent Transportation Systems (ITS). 99 1-10
Heiler, M and Schnörr, C (2005). Reverse-Convex Programming for Sparse Image Codes. Proc.~Int.~Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'05). Springer. 3757 600-616
Leue, C, Wenig, M, Platt, U, Jähne, B, Geißler, P and Haußecker, H (1999). Retrieval of Atmospheric Trace Gas Concentrations. Handbook of Computer Vision and Applications. Academic Press. 3: Systems and Applications 783-805
Wenig, M, Kuhl, S, Beirle, S, Bucsela, E, Jähne, B, Platt, U, Gleason, J and Wagner, T (2004). Retrieval and analysis of stratospheric NO$_2$ from the Global Ozone Monitoring Experiment. J. Geophys. Res. 109 D04315, 1--11
Saussen, B (2007). Retention Time Domain Registration Of Liquid Chromatography/mass Spectrometry Data. University of Heidelberg
Jähne, B, Haußecker, H, Platt, U, Schurr, U and Stitt, M (1997). The research unit (Forschergruppe) Image Sequence Processing to Study Dynamical Processes. Proc.\ 3D Image Analysis and Synthesis'97, Erlangen (Germany), November 17--18, 1997. infix. 107--114
Jähne, B, Jähne, B and Haußecker, H (2000). Representation of multidimensional signals. Computer Vision and Applications. A Guide for Students and Practitioners. Academic Press. 211--272
Schnörr, (1996). Representation Of Images By A Convex Variational Diffusion Approach. FB Informatik
Schnörr, (1996). Repräsentation von Bilddaten mit einem konvexen Variationsansatz. Mustererkennung 1996. Springer-Verlag. 21--28
Liss, P S, Watson, A J, Bock, E J, Jähne, B, Asher, W E, Frew, N M, Hasse, L, Korenowski, G M, Merlivat, L, Phillips, L F, Schlüssel, P and Woolf, D K (1997). Report Group 1 - Physical processes in the microlayer and the air-sea exchange of trace gases. The Sea Surface and Global Change. Cambridge University Press. 1--33
Zhang, H, Hamprecht, F A and Amann, A (2005). Report about VOCs Dataset's Analysis based on Random Forests. Proceedings of the HPC-Asia05. IEEE Computer Society Press. 603-607PDF icon Technical Report (232.13 KB)
Withopf, D (2007). Reliable Real-Time Vehicle Detection and Tracking. IWR, Fakultät für Mathematik und Informatik, Univ.\ Heidelberg.
Köthe, (2008). Reliable Low-Level Image Analysis. Habilitation thesis. Department Informatik, University of Hamburg, HamburgPDF icon Technical Report (12.44 MB)
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
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
Reinecke, H, Fantana, N L, Haußecker, H and Jähne, B (1997). Rekonstruktion von Schreiberkurven. Mustererkennung 1997. Springer. 527--536
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)
Lellmann, J and Schnörr, C (2011). Regularizers for Vector-Valued Data and Labeling Problems in Image Processing. Control Systems and Computers. 2 43--54
Spies, H, Jähne, B and Barron, J L (2000). Regularised range flow. European Conference on Computer Vision (ECCV). Springer. 2 785--799
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.
Lang, S and Ommer, B (2018). Reflecting on How Artworks Are Processed and Analyzed by Computer Vision. European Conference on Computer Vision (ECCV). Springer
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.
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. icon Technical Report (2.43 MB)
Wanner, S and Goldlücke, B (2013). Reconstructing Reflective and Transparent Surfaces from Epipolar Plane Images. Pattern Recognition. Springer. 1--10
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)
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)
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
Strzodka, R and Garbe, C S (2004). Real-time motion estimation and visualization on graphics cards. Proceedings IEEE Visualization 2004. 545--552
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
Weickert, J and Schnörr, C (1999). Räumlich--zeitliche Berechnung des optischen Flusses mit nichtlinearen flussabhängigen Glattheitstermen. Mustererkennung 1999. Springer. 317--324
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
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
Spies, H, Jähne, B and Barron, J L (2002). Range flow estimation.. Computer Vision and Image Understanding. 85 209--231