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Institute for Visualization and Interactive Systems   

Welcome to the Homepage of

Michael Stoll

Research Assistant

   University of Stuttgart

Position: Ph.D. Student
Phone: +49-711-685-88364
Fax: +49-711-685-88340
E-mail: michael.stoll -at- vis.uni-stuttgart.de
Address: Intelligent Systems Department
Institute for Visualization and Interactive Systems
University of Stuttgart, Universitätsstraße 38
70569 Stuttgart, Germany
Office: Room 1.465, Computer Science Building


  • Stereo Reconstruction
  • Optical Flow

Journals

Conferences

  • European Conference on Computer Vision (ECCV)
  • IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • International Conference on Energy Minimization Methods in Computer Vision
    and Pattern Recognition (EMMCVPR)
  • International Conference on Scale Space and Variational Methods in Computer Vision (SSVM)
  • German Conference on Pattern Recognition (GCPR)
  • Conference on Graphics, Pattern and Images (SIBGRAPI)
  • Inverse Rendering Workshop at the International Conference on Computer Vision (ICCV-IR)
  • Optical Flow and Stereo Workshop at the European Conference on Computer Vision (ECCV-W)

Conference Papers

  1. 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, Springer, Berlin, 2017, accepted for publication.
  2. 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, Springer, Berlin, 2017, accepted for publication.
  3. D. Maurer, M. Stoll, A. Bruhn:
    Order-Adaptive and Illumination Aware Variational Optical Flow Refinement.
    In Proc. 28th British Machine Vision Conference
    BMVC 2017, London, UK, September 2017 - K. Mikolajczyk, G. Brostow, T.-K. Kim, S. Zafeiriou (Eds.)
    BMVA Press, 2017, accepted for publication.
    See also: Supplementary Material [26MB].
  4. 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 2017, Los Angeles, July 2017 - H. Winnemoeller, L. Bartram (Eds.)
    ACM Digital Library, 2017, accepted for publication.
    Awarded an EXPRESSIVE 2017 Best Paper Award.
  5. D. Maurer, M. Stoll, A. Bruhn:
    Order-Adaptive Regularisation for Variational Optical Flow: Global, Local and in Between.
    In Proc. 6th International Conference on Scale Space and Variational Methods in Computer Vision
    SSVM 2017, Kolding, Denmark, June 2017 - F. Lauze, Y. Dong, A. B. Dahl (Eds.)
    Lecture Notes in Computer Science, Vol. 10302, 550-562, Springer, Berlin, 2017.
  6. D. Maurer, M. Stoll, S. Volz, P. Gairing, A. Bruhn:
    A Comparison of Isotropic and Anisotropic Second Order Regularisers for Optical Flow.
    In Proc. 6th International Conference on Scale Space and Variational Methods in Computer Vision
    SSVM 2017, Kolding, Denmark, June 2017 - F. Lauze, Y. Dong, A. B. Dahl (Eds.)
    Lecture Notes in Computer Science, Vol. 10302, 537-549, Springer, Berlin, 2017.
  7. M. Stoll, S. Volz, D. Maurer, A. Bruhn:
    A Time-Efficient Optimisation Framework for Parameters of Optical Flow Methods.
    In Proc. 20th Scandinavian Conference on Image Analysis
    SCIA 2017, Tromsø Norway, June 2017 - P. Sharma, F. M. Bianchi (Eds.)
    Lecture Notes in Computer Science, Vol. 10269, 41-53, Springer, Berlin, 2017.
  8. 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. 13th European Conference on Computer Vision
    ECCV 2014, Zurich, Switzerland, September 2014
    Lecture Notes in Computer Science, Vol. 8689, Springer, Berlin, 455-471, 2014.

  9. 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
    IEEE Computer Society Press, 2013.

  10. M. Stoll, S. Volz, A. Bruhn
    Joint Trilateral Filtering for Multiframe Optical Flow.
    In Proc. 20th IEEE International Conference on Image Processing
    ICIP 2013, Melbourne, Australia, September 2013
    IEEE Computer Society Press, 3845-3849, 2013.

  11. M. Stoll, S. Volz, A. Bruhn
    Adaptive Integration of Feature Matches into Variational Optical Flow Methods.
    In Proc. 11th Asian Conference on Computer Vision
    ACCV 2012, Daejeon, Korea, November 2012 - K. M. Lee, J. Rheg, Y. Matshushita, Z. Hu (Eds.)
    Lecture Notes in Computer Science, Springer, Berlin, 1-14, 2013.
    See also: Supplementary Material.

  12. S. Metzger, M. Stoll, K. Hose, R. Schenkel
    LUKe and MIKE: Learning from User Knowledge and Managing Interactive Knowledge Extraction.
    In Proc. 21st ACM International Conference on Information and Knowledge Management
    CIKM 2012, Maui, USA, Oct./Nov. 2012 - X.-W. Chen, G. Lebanon, H. Wang, M. J. Zaki (Eds.)
    Demo Paper, ACM Press, 2671-2673, 2012.

  13. M. Stoll, K. Hose, S. Metzger, R. Schenkel
    Interaktive Wissensextraktion und Wissenssuche.
    In M. Spiliopoulou, A. Nürnberger, R. Schult (Eds.):
    Proc. LWA Workshop on Information Retrieval
    Working Notes of the LWA 2011 - Learning, Knowing, Adaptation, 2011.


  14. Theses


  15. M. Stoll
    MIKE - Managing Interactive Knowledge Extraction.
    Master Thesis in Computer Science, Department of Mathematics and Computer Science,
    Saarland University, Saarbrücken, April, 2012.

  16. M. Stoll
    Large Displacement Optical Flow.
    Master Thesis in Visual Computing, Department of Mathematics and Computer Science,
    Saarland University, Saarbrücken, November, 2011.

  17. M. Stoll
    Hilbertfunktionen und Betti-Tabellen mit Anwendung auf die Konstruktion von Kurven.
    Bachelor Thesis in Mathematics, Department of Mathematics and Computer Science,
    Saarland University, Saarbrücken, March, 2010.

  18. M. Stoll
    Improving the Prediction of Defect-Localization Methods by Intelligent Choices of Test Runs.
    Bachelor Thesis in Computer Science, Department of Mathematics and Computer Science,
    Saarland University, Saarbrücken, December, 2008.


Master/Diploma Students

  1. Oliver Naumann (2015)
  2. Steffen Nüssle (2017)



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