Logo of Computer Vision and Intelligent Systems Group
Institute for Visualization and Interactive Systems   

Publications of the CVIS Group

   University of Stuttgart

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. The technical reports available on this web page are not necessarily identical with the final journal papers.

  1. H. Men, H. Lin, V. Hosu, D. Maurer, A. Bruhn, D. Saupe:
    Visual quality assessment for motion compensated frame interpolation.
    International Conference on Quality of Multimedia Experience (QoMEX).
    IEEE Press, 2019.
  2. T. Brox, A. Bruhn, M. Fritz (Eds.):
    Pattern Recognition.
    (Proc. German Conference on Pattern Recognition 2018).
    Lecture Notes in Computer Science, Vol. 11269, Springer, 2019.
  3. D. Maurer, N. Marniok, B. Goldlücke, A. Bruhn:
    Structure-from-Motion aware PatchMatch for Adaptive Optical Flow Estimation.
    In Proc. European Conference on Computer Vision (ECCV).
    Lecture Notes in Computer Science, Vol. 11212, 575-592, Springer, 2018.
  4. D. Maurer, A. Bruhn:
    ProFlow: Learning to Predict Optical Flow.
    In Proc. British Machine Vision Conference (BMVC).
    BMVA Press, 2018.
    See also: Supplementary Material.
    Awarded a CVPR 2018 Robust Vison Challenge Runner-Up Award.
  5. D. Maurer, M. Stoll, A. Bruhn:
    Directional Priors for Multi-Frame Optical Flow Estimation.
    In Proc. British Machine Vision Conference (BMVC).
    BMVA Press, 2018.
    See also: Supplementary Material.
  6. D. Maurer, Y. C. Ju, M. Breuß, A. Bruhn:
    Combining Shape from Shading and Stereo:
    A Joint Variational Method for Estimating Depth, Illumination and Albedo
    .
    International Journal of Computer Vision (IJCV), online first, March 2018.
    (A read-only version can be found here.)
  7. M. Stoll, D. Maurer, A. Bruhn:
    Variational large displacement optical flow without feature matches.
    In Proc. Int. Conf. on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR).
    Lecture Notes in Computer Science, Vol. 10746, 79-92, Springer, 2017.
  8. M. Stoll, D. Maurer, S. Volz, A. Bruhn:
    Illumination-aware large displacement optical flow.
    In Proc. Int. Conf. on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR).
    Lecture Notes in Computer Science, Vol. 10746, 139-154, Springer, 2017.
  9. D. Maurer, M. Stoll, A. Bruhn:
    Order-adaptive and illumination-aware variational optical flow refinement.
    In Proc. British Machine Vision Conference (BMVC).
    BMVA Press, 2017, accepted for publication.
    See also: Supplementary Material [26MB].
  10. K. Kurzhals, M. Stoll, A. Bruhn, D. Weiskopf:
    FlowBrush: Optical Flow Art.
    In Proc. Symposium on Computational Aesthetics, Sketch-Based Interfaces and Modeling, and Non-Photorealistic Animation and Rendering (EXPRESSIVE, co-located with SIGGRAPH). ACM Digital Library, 2017.
    Awarded an EXPRESSIVE 2017 Best Paper Award.
  11. D. Maurer, M. Stoll, A. Bruhn:
    Order-adaptive regularisation for variational optical flow: global, local and in between.
    In Proc. International Conference on Scale Space and Variational Methods in Computer Vision (SSVM).
    Lecture Notes in Computer Science, Vol. 10302, 550-562, Springer, 2017.
  12. D. Maurer, M. Stoll, S. Volz, P. Gairing, A. Bruhn:
    A comparison of isotropic and anisotropic second order regularisers for optical flow.
    In Proc. International Conference on Scale Space and Variational Methods in Computer Vision (SSVM).
    Lecture Notes in Computer Science, Vol. 10302, 537-549, Springer, 2017.
  13. M. Stoll, S. Volz, D. Maurer, A. Bruhn:
    A time-efficient optimisation framework for parameters of optical flow methods.
    In Proc. Scandinavian Conference on Image Analysis (SCIA).
    Lecture Notes in Computer Science, Vol. 10269, 41-53, Springer, 2017.
  14. Y.-C. Ju:
    PDE-based vs. Variational Methods for Perspective Shape from Shading.
    Ph.D. Thesis. Institute for Visualization and Interactive Systems, University of Stuttgart, 2017.

  15. D. Maurer, Y. C. Ju, M. Breuß, A. Bruhn:
    Combining Shape from Shading and Stereo:
    A Variational Approach for the Joint Estimation of Depth, Illumination and Albedo
    .
    In Proc. British Machine Vision Conference (BMVC).
    BMVA Press, Art. 76, 2016.
    See also: Supplementary Material [60MB].
  16. Y. C. Ju, D. Maurer, M. Breuß, A. Bruhn:
    Direct variational perspective shape from shading with Cartesian depth parametrisation.
    Perspectives on Shape From Shading.
    Mathematics and Visualization, 43-72, Springer, Berlin, 2016.
    (Also available as ArXiv Preprint 1505.06163, 2015.)
  17. J. Weickert, S. Grewenig, C. Schroers, A. Bruhn:
    Cyclic schemes for PDE-based image analysis.
    International Journal of Computer Vision (IJCV), 2016,
    (Also available as Technical Report No. 327, Department of Mathematics, Saarland University, Germany, 2015.)
  18. D. Maurer, Y. C. Ju, M. Breuß, A. Bruhn:
    An efficient linearisation approach for variational perspective shape from shading.
    In Proc. German Conference on Pattern Recognition (GCPR).
    Lecture Notes in Computer Science, Vol. 9358, 249-261, Springer, Berlin, 2015.
  19. Y. C. Ju, A. Bruhn, M. Breuß:
    Variational perspective shape from shading.
    In Proc. International Conference on Scale Space and Variational Methods in Computer Vision (SSVM).
    Lecture Notes in Computer Science, Vol. 9087, 538-550, Springer, Berlin, 2015.
  20. O. Demetz, M. Stoll, S. Volz, J. Weickert, A. Bruhn:
    Learning brightness transfer functions for the joint recovery of illumination changes and optical flow.
    In Proc. European Conference on Computer Vision (ECCV).
    Lecture Notes in Computer Science, Vol. 8689, 455-471, Springer, 2014.
  21. C. Schmaltz, P. Peter, M. Mainberger, F. Ebel, J. Weickert, A. Bruhn:
    Understanding, optimising, and extending data compression with anisotropic diffusion.
    International Journal of Computer Vision (IJCV), Vol. 108, No. 3, 222-240, July 2014.
    (Revised version of Technical Report No. 329, Department of Mathematics, Saarland University, Germany, 2013.)
  22. A. Bruhn, T. Pock, X.-C- Tai (Eds.):
    Efficient Algorithms for Global Optimization Problems in Computer Vision.
    Lecture Notes in Computer Science, Vol. 8293, Springer, Berlin, 2014.
  23. N. Persch, A. Elhayek, M. Welk, A. Bruhn, S. Grewenig, K. Böse, A. Kraegeloh, J. Weickert:
    Enhancing 3-D cell structures in confocal and STED microscopy:
    a joint model for interpolation, deblurring and anisotropic smoothing
    .
    Measurement Science and Technology (MST), 2013.
    (Revised version of Technical Report No. 321, Department of Mathematics, Saarland University, Germany, 2013.)
  24. M. Stoll, R. Krüger, T. Ertl, A. Bruhn:
    Racecar tracking and its visualization using sparse data.
    In Proc. IEEE VIS Workshop on Sports Data Visualization (VIS-WSDV).
    IEEE Computer Society Press, 2013.
  25. M. Stoll, S. Volz, A. Bruhn:
    Joint trilateral filtering for multiframe optical flow.
    In Proc. International Conference on Image Processing (ICIP).
    IEEE Computer Society Press, 3845-3849, 2013.
  26. Y.-C. Ju, S. Tozza, M. Breuß, A. Bruhn, A. Kleefeld:
    Generalised perspective shape from shading with Oren-Nayar reflectance.
    In Proc. British Machine Vision Conference (BMVC).
    BMVA Press, Art. 14, 2013.
  27. S. Galliani, Y. C. Ju, M. Breuß, A. Bruhn:
    Generalised perspective shape from shading in spherical coordinates.
    In Proc. International Conference on Scale Space and Variational Methods in Computer Vision (SSVM).
    Lecture Notes in Computer Science, Vol. 7893, 222-233, Springer, Berlin, 2013.
  28. M. Stoll, S. Volz, A. Bruhn:
    Adaptive integration of feature matches into variational optical flow methods.
    Proc. Asian Conference on Computer Vision (ACCV).
    Lecture Notes in Computer Science, 1-14, Springer, Berlin, 2013.
    See also: Supplementary Material.
  29. L. Valgaerts, C. Wu, A. Bruhn, H.-P. Seidel, C. Theobalt:
    Lightweight binocular facial performance capture under uncontrolled lighting.
    ACM Transactions on Graphics (Proc. SIGGRAPH Asia), Vol. 31, No. 6, Art. 187, 2012.
  30. S. Metzger, M. Stoll, K. Hose, R. Schenkel:
    LUKe and MIKE: Learning from user knowledge and managing interactive knowledge extraction.
    In X.-W. Chen, G. Lebanon, H. Wang, M. J. Zaki (Eds.):
    In Proc. International Conference on Information and Knowledge Management (CIKM).
    Demo Paper, 2671-2673, ACM Press, 2012.

  31. P. Gwosdek, H. Zimmer, S. Grewenig, A. Bruhn, J. Weickert:
    A highly efficient GPU implementation for variational optic flow based on the Euler-Lagrange framework.
    In Proc. ECCV Workshop on Computer Vision with GPUs (ECCV-WCVGPU).
    Lecture Notes in Computer Science, Vol. 6554, 372-382, Springer, Berlin, 2012.
    (Revised version of Technical Report No. 267, Department of Mathematics, Saarland University, Germany, 2010.)
    See also: Supplementary Material Webpage.
  32. Y.-C. Ju, M. Breuß, A. Bruhn, S. Galliani:
    Shape from shading for rough surfaces: Analysis of the Oren-Nayar model.
    In Proc. British Machine Vision Conference (BMVC).
    BMVA Press, Art. 104, 2012.
  33. S. Galliani, M. Breuß, Y.-C. Ju:
    Fast and robust surface normal integration by a discrete eikonal equation.
    In Proc. British Machine Vision Conference (BMVC).
    BMVA Press, Art. 106, 2012.
  34. C. Schroers, H. Zimmer, L. Valgaerts, A. Bruhn, O. Demetz, J. Weickert:
    Anisotropic range image integration.
    In Proc. Joint German and Austrian Conference on Pattern Recognition (DAGM/ÖAGM).
    Lecture Notes in Computer Science, Vol. 7476, 73-82, Springer, Berlin, 2012.
    Awarded a DAGM-OAGM 2012 Paper Prize.
  35. L. Lau Rakêt, L. Roholm, A. Bruhn, J. Weickert:
    Motion compensated frame interpolation with a symmetrical optical flow constraint.
    In Proc. International Symposium on Visual Computing (ISVC).
    Lecture Notes in Computer Science, Vol. 7431, 447-457, Springer, Berlin, 2012.
  36. L. Valgaerts, A. Bruhn, M. Mainberger, J. Weickert:
    Dense versus sparse approaches for estimating the fundamental matrix.
    International Journal of Computer Vision (IJCV), Vol. 96, No. 2, 212-234, January 2012.
    (Revised version of Technical Report No. 263, Department of Mathematics, Saarland University, Germany, 2010.)
  37. O. Demetz, J. Weickert, A. Bruhn, H. Zimmer:
    Optic flow scale space.
    In Proc. International Conference on Scale Space and Variational Methods in Computer Vision (SSVM).
    Lecture Notes in Computer Science, Vol. 6667, 713-724, Springer, Berlin, 2012.
  38. P. Gwosdek, S. Grewenig, A. Bruhn, J. Weickert:
    Theoretical foundations of Gaussian convolution by extended box filtering.
    In Proc. International Conference on Scale Space and Variational Methods in Computer Vision (SSVM).
    Lecture Notes in Computer Science, Vol. 6667, 447-458, Springer, Berlin, 2012.
  39. S. Volz, A. Bruhn, L. Valgaerts, H. Zimmer:
    Modeling temporal coherence for optical flow.
    In Proc. International Conference on Computer Vision (ICCV).
    IEEE Computer Society Press, 1116-1123, 2011.
    See also: Supplementary Material Webpage.
  40. M. Breuß, Y.C. Ju:
    Shape from shading with specular highlights: analysis of the Phong model.
    In Proc. International Conference on Image Processing (ICIP).
    IEEE Computer Society Press, 9-12, 2011.
  41. F. Faubel, M. Georges, K. Kumatani, A. Bruhn, D. Klakow:
    Improving hands-free speech recognition in a car through audio-visual voice activity detection.
    In Proc. Joint Workshop on Hands-free Speech Communication and Microphone Arrays (HSCMA).
    IEEE Xplore, 70-75, 2011.
  42. M. Mainberger, A. Bruhn, J. Weickert, S. Forchhammer:
    Edge-based compression of cartoon-like images with homogeneous diffusion.
    Pattern Recognition (PR), Vol. 44, No. 9, 1859-1873, September 2011.
    (Also available as Technical Report No. 269, Department of Mathematics, Saarland University, Germany, 2010.)
    Invited Paper.
  43. H. Zimmer, A. Bruhn, J. Weickert:
    Optic flow in harmony.
    International Journal of Computer Vision (IJCV), Vol. 93, No. 3, 368-388, July 2011.
    (Revised version of Technical Report No. 272, Department of Mathematics, Saarland University, Germany, 2010.)
  44. H. Zimmer, A. Bruhn, J. Weickert:
    Freehand HDR imaging of moving scenes with simultaneous resolution enhancement.
    Computer Graphics Forum (CGF, Proc. EUROGRAPHICS), Vol. 30, No. 2, April 2011.
    (Revised version of Technical Report No. 286, Department of Mathematics, Saarland University, Germany, 2010.)
    See also: Supplementary Material Webpage.
  45. C. Schmaltz, P. Gwosdek, A. Bruhn, J. Weickert:
    Electrostatic halftoning.
    Computer Graphics Forum (CGF), Vol. 29, No. 8, 2313-2327, December 2010.
    (Revised version of Technical Report No. 260, Department of Mathematics, Saarland University, Germany, 2010.)
    See also: Supplementary Material Webpage.
  46. P. Gwosdek, A. Bruhn, J. Weickert:
    Variational optic flow on the Sony PlayStation 3.
    Journal of Real-Time Image Processing (JRTIP), Vol. 5, No. 3, 163-177, 2010.
    (Revised version of Technical Report No. 233, Department of Mathematics, Saarland University, Germany, 2009.)
  47. S. Grewenig, J. Weickert, A. Bruhn:
    From box filtering to fast explicit diffusion.
    In Proc. German Conference on Pattern Recognition (DAGM).
    Lecture Notes in Computer Science, Vol. 6376, 533-542, Springer, Berlin, 2010.
    Awarded the DAGM 2010 Main Prize (Best Paper Award).
  48. L. Valgaerts, A. Bruhn, H. Zimmer, J. Weickert, C. Stoll, C. Theobalt:
    Joint estimation of motion, structure and geometry from stereo sequences.
    In Proc. European Conference on Computer Vision (ECCV).
    Lecture Notes in Computer Science, Vol. 6314, 568-581, Springer, Berlin, 2010.
    See also: Supplementary Material Webpage.
  49. C. Hauger, H. Weigand, J. Weickert, A. Bruhn:
    Medizinisch optisches Beobachtungsgerät und Verfahren zum Erstellen einer stereoskopischen Zwischenperspektive in einem derartigen Gerät.
    Patent DE 10 2008 024 732 B4 2010.04.01, April 2010.
  50. H. Zimmer, A. Bruhn, J. Weickert, L. Valgaerts, A. Salgado, B. Rosenhahn, H.-P. Seidel:
    Complementary optic flow.
    In Proc. Int. Conf. on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR).
    Lecture Notes in Computer Science, Vol. 5681, 207-220, Springer, Berlin, 2009.
  51. C. Schmaltz, J. Weickert, A. Bruhn:
    Beating the quality of JPEG 2000 with anisotropic diffusion.
    In Proc. German Confernce on Pattern Recognition (DAGM).
    Lecture Notes in Computer Science, Vol. 5748, 452-461, Springer, Berlin, 2009.
  52. M. Ghodstinat, A. Bruhn, J. Weickert:
    Deinterlacing with motion-compensated anisotropic diffusion.
    Statistical and Geometrical Approaches to Visual Motion Analysis.
    Lecture Notes in Computer Science, Vol. 5604, 91-106, Springer, Berlin, 2009.
  53. H. Zimmer, A. Bruhn, L. Valgaerts, M. Breuß, J. Weickert, B. Rosenhahn, H.-P. Seidel:
    PDE-based anisotropic disparity-driven stereo vision.
    In Proc. International Workshop on Vision, Modeling, and Visualization (VMV).
    AKA Heidelberg, 263-272, 2008.
  54. P. Gwosdek, A. Bruhn, J. Weickert:
    High performance parallel optical flow algorithms on the Sony Playstation 3.
    In Proc. International Workshop on Vision, Modeling, and Visualization (VMV).
    AKA, Heidelberg, 253-262, 2008.
  55. I. Galić, J. Weickert, M. Welk, A. Bruhn, A. Belyaev, H.-P. Seidel:
    Image compression with anisotropic diffusion.
    Journal of Mathematical Imaging and Vision (JMIV), Vol. 31, 255–269, 2008.
    Invited Paper.
  56. L. Valgaerts, A. Bruhn, J. Weickert:
    A variational model for the joint recovery of the optical flow and the fundamental matrix.
    In Proc. German Conference on Pattern Recognition (DAGM).
    Lecture Notes in Computer Science, Vol. 5096, 314-324, Springer, Berlin, 2008.
  57. M. Mainberger, A. Bruhn, J. Weickert:
    Is dense optical flow useful to compute the fundamental matrix? - Errata.
    In Proc. International Conference on Image Analysis and Recognition (ICIAR).
    Lecture Notes in Computer Science, Vol. 5112, 630-639, Springer, Berlin, 2008.
  58. A. Bruhn:
    Bewegungsschätzung in Echtzeit mit Optimierungsansätzen.
    it - Information Technology, Vol. 50, No. 1, 66-69, Oldenbourg Wissenschaftsverlag, 2008.
    Invited Paper.
  59. Y. Mileva, A. Bruhn, J. Weickert:
    Illumination-robust variational optical flow with photometric invariants.
    In Proc. German Conference on Pattern Recognition (DAGM).
    Lecture Notes in Computer Science, Vol. 4713, 152-162, Springer, Berlin, 2007.
  60. A. Bruhn:
    Variationsansätze zur Bewegungsschätzung: Präzise Modellierung und effiziente Numerik.
    Ausgezeichnete Informatikdissertationen 2006.
    GI-Edition Lecture Notes in Informatics (LNI), Vol. D-7, 9-18, Gesellschaft für Informatik, Bonn, 2007.
    Invited Paper.
  61. N. Slesareva, T. Bühler, K. Hagenburg, J. Weickert, A. Bruhn, Z. Karni, H.-P. Seidel:
    Robust variational reconstruction from multiple views.
    In Proc. Scandinavian Conference on Image Analysis (SCIA).
    Lecture Notes in Computer Science, Vol. 4522, 173-182, Springer, Berlin, 2007.
  62. O. Demetz, J. Weickert, A. Bruhn, M. Welk:
    Beauty with variational methods: An optic flow approach to hairstyle simulation.
    In Proc. International Conference on Scale Space and Variational Methods in Computer Vision (SSVM).
    Lecture Notes in Computer Science, Vol. 4485, 825-836, Springer, Berlin, 2007.
  63. O. Vogel, A. Bruhn, J. Weickert, S. Didas:
    Direct shape-from-shading with adaptive higher order regularisation.
    In Proc. International Conference on Scale Space and Variational Methods in Computer Vision (SSVM).
    Lecture Notes in Computer Science, Vol. 4485, 871-882, Springer, Berlin, 2007.
  64. B. Burgeth, A. Bruhn, S. Didas, J. Weickert, M. Welk:
    Morphology for tensor data: Ordering versus PDE-based approach.
    Image and Vision Computing (IMAVIS), Vol. 25, No. 4, 496-511, 2007.
    (Revised version of Technical Report No. 162, Department of Mathematics, Saarland University, Germany, 2005.)
  65. B. Burgeth, N. Papenberg, A. Bruhn, M. Welk, J. Weickert:
    Mathematical morphology for matrix fields induced by the Loewner ordering in higher dimensions.
    Signal Processing (SIGPRO), Vol. 87, No. 2, 277-290, 2007.
    (Revised version of Technical Report No. 161, Department of Mathematics, Saarland University, Germany, 2005.)
    Invited Paper.
  66. A. Bruhn, J. Weickert, T. Kohlberger, C. Schnörr:
    A multigrid platform for real-time motion computation with discontinuity-preserving variational methods.
    International Journal of Computer Vision (IJCV), Vol. 70, No. 3, 257-277, 2006.
    Invited Paper.

  67. J. Weickert, A. Bruhn, T. Brox, N. Papenberg:
    A survey on variational optic flow methods for small displacements.
    Mathematical Models for Registration and Applications to Medical Imaging, 103-136, Springer, Berlin, 2006.
    (Revised version of Technical Report No. 152, Department of Mathematics, Saarland University, Germany, 2005.)
  68. N. Papenberg, A. Bruhn, T. Brox, S. Didas, J. Weickert:
    Highly accurate optic flow computation with theoretically justified warping.
    International Journal of Computer Vision (IJCV), Vol. 67, No. 2, 141-158, 2006.
    (Revised version of Technical Report No. 124, Department of Mathematics, Saarland University, Germany, 2005.)
  69. T. Brox, A. Bruhn, J. Weickert:
    Variational motion segmentation with level sets.
    In Proc. European Conference on Computer Vision (ECCV).
    Lecture Notes in Computer Science, Vol. 3951, 471-483, Springer, Berlin, 2006.
  70. A. Bruhn, J. Weickert:
    A confidence measure for variational optic flow methods.
    Geometric Properties from Incomplete Data, Springer, 283-297, Dordrecht, 2006.
    (Revised version of Technical Report No. 106, Department of Mathematics, Saarland University, Germany, 2004.)
  71. P. Mrázek, J. Weickert, A. Bruhn:
    On robust estimation and smoothing with spatial and tonal kernels.
    Geometric Properties from Incomplete Data, 334-352, Springer, Dordrecht, 2006.
    (Revised version of Preprint No. 51, DFG Priority Programme 1114, University of Bremen, Germany, 2004.)
  72. N. Slesareva, A. Bruhn, J. Weickert:
    Optic flow goes stereo: A variational method for estimating discontinuity-preserving dense disparity maps.
    In Proc. German Conference on Pattern Recognitionn (DAGM).
    Lecture Notes in Computer Science, Vol. 3663, 33-40, Springer, Berlin, 2005.
    Awarded a DAGM 2005 Paper Prize.
  73. T. Kohlberger, C. Schnörr, A. Bruhn, J. Weickert:
    Domain decomposition for variational optical flow computation.
    IEEE Transactions on Image Processing (TIP), Vol. 14, No. 8, 1125-1137, August 2005.
  74. I. Galić, J. Weickert, M. Welk, A. Bruhn, A. Belyaev, H.-P. Seidel:
    Towards PDE-based image compression.
    In Proc. International Workshop on Variational, Geometric, and Level Set Methods in Computer Vision (VLSM).
    Lecture Notes in Computer Science, Vol. 3752, 37-47, Springer, Berlin, 2005.
  75. A. Bruhn, J. Weickert:
    Towards ultimate motion estimation: Combining highest accuracy with real-time performance.
    In Proc. International Conference on Computer Vision (ICCV).
    IEEE Computer Society Press, 749-755, 2005.
  76. T. Kohlberger, C. Schnörr, A. Bruhn, J. Weickert:
    Domain decomposition for nonlinear problems: a control-theoretic approach.
    Technical Report 2005/3, Computer Science Series, University of Mannheim, Germany, 2005.
  77. A. Bruhn, J. Weickert, C. Feddern, T. Kohlberger, C. Schnörr:
    Variational optic flow computation in real-time.
    IEEE Transactions on Image Processing (TIP), Vol. 14, No. 5, 608-615, 2005.
    (Revised version of Technical Report No. 89, Department of Mathematics, Saarland University, Germany, 2003.)
  78. B. Burgeth, N. Papenberg, A. Bruhn, M. Welk, C. Feddern, J. Weickert:
    Morphology for higher-dimensional tensor data via Loewner ordering.
    In Proc. International Symposium on Mathematical Morphology (ISMM).
    Computational Imaging and Vision, Vol. 30, 407-416, Springer, Dordrecht, 2005.
  79. A. Bruhn, J. Weickert, T. Kohlberger, C. Schnörr:
    Discontinuity-preserving computation of variational optic flow in real-time.
    In Proc. International Conferece on Scale-Space and PDE Methods in Computer Vision (SSVM).
    Lecture Notes in Computer Science, Vol. 3459, 279-290, Springer, Berlin, 2005.
  80. A. Bruhn, J. Weickert, C. Schnörr:
    Lucas/Kanade meets Horn/Schunck: Combining local and global optic flow methods - Errata.
    International Journal of Computer Vision (IJCV), Vol. 61, No. 3, 211-231, 2005.
  81. T. Brox, A. Bruhn, N. Papenberg, J. Weickert:
    High accuracy optical flow estimation based on a theory for warping.
    In Proc. European Confernece on Computer Vision (ECCV).
    Lecture Notes in Computer Science, Vol. 3024, 25-36, Springer, Berlin, 2004.
    Awarded the ECCV 2004 Longuet-Higgins Best Paper Award.
  82. T. Kohlberger, C. Schnörr, A. Bruhn, J. Weickert:
    Parallel variational motion estimation by domain decomposition and cluster computing..
    In Proc. European Conference on Computer Vision (ECCV).
    Lecture Notes in Computer Science, Vol. 3024, pringer, 205-216, Berlin, 2004.
  83. A. Bruhn, T. Jakob, M. Fischer, T. Kohlberger, J. Weickert, U. Brüning, C. Schnörr:
    High performance cluster computing with 3-D nonlinear diffusion filters.
    Real-Time Imaging (RTI) , Vol. 10, No. 1, 41-51, 2004.
    (Revised version of Technical Report No. 87, Department of Mathematics, Saarland University, Germany, 2003.)
  84. N. Papenberg, A. Bruhn, T. Brox, J. Weickert:
    Numerical justification for multiresolution optical flow computation.
    In Proc. International Workshop on Computer Vision and Image Analysis (IWCVIA).
    Vol. 0026 of Cuadernos del Instituto Universitario de Ciencias y Tecnologias Ciberneticas,
    University of Las Palmas de Gran Canaria, Spain, 7-12, 2004.
  85. J. Weickert, A. Bruhn, N. Papenberg, T. Brox:
    Variational optic flow computation: From continuous models to algorithms.
    In Proc. International Workshop on Computer Vision and Image Analysis (IWCVIA).
    Vol. 0026 of Cuadernos del Instituto Universitario de Ciencias y Tecnologias Ciberneticas,
    University of Las Palmas de Gran Canaria, Spain, 1-6, 2004.
  86. D. Slogsnat, M. Fischer, A. Bruhn, J. Weickert, U. Brüning:
    Low level parallelization of nonlinear diffusion filtering algorithms for cluster computing environments.
    In Proc. European Conference on Parallel Processing (EURO-PAR).
    Lecture Notes in Computer Science, Vol. 2790, 481-490, Springer, Berlin, 2003.
  87. T. Kohlberger, C. Schnörr, A. Bruhn, J. Weickert:
    Domain decomposition for parallel variational optic flow computation.
    In Proc. German Conference on Pattern Recognition (DAGM).
    Lecture Notes in Computer Science, Vol. 2781, 196-202, Springer, Berlin, 2003.
  88. A. Bruhn, J. Weickert, C. Feddern, T. Kohlberger and C. Schnörr:
    Real-time optic flow computation with variational methods.
    In Proc. International Conference on Computer Analysis of Images and Patterns (CAIP).
    Lecture Notes in Computer Science, Vol. 2756, 222-229, Springer, Berlin, 2003.
  89. A. Bruhn, J. Weickert, C. Schnörr:
    Combining the advantages of local and global optic flow methods.
    In Proc. German Conference on Pattern Recognition (DAGM).
    Lecture Notes in Computer Science, Vol. 2449, 454-462, Springer, Berlin, 2002.
    Awarded a DAGM 2002 Paper Prize.
  90. A. Bruhn, T. Jakob, M. Fischer, T. Kohlberger, J. Weickert, U. Brüning, C. Schnörr:
    Designing 3-D nonlinear diffusion filters for high performance cluster computing.
    In Proc. German Conference on Pattern Recognition (DAGM).
    Lecture Notes in Computer Science, Vol. 2449, 290-297, Springer, Berlin, 2002.

CVIS Group
©2012-2018
The author is not
responsible for
the content of
external pages.