Mitarbeiter

Herr  M. Sc.
Daniel Maurer
Wiss. Mitarbeiter Abteilung Intelligente Systeme

Dieses Bild zeigt  DanielMaurer
Telefon+49 (711) 685-88325
Raum1.061
E-Mail
Adresse
Universität Stuttgart
VIS (Informatik-Gebäude)
Universitätsstraße 38
70569 Stuttgart
Deutschland
Publikationen:
  1. 2017

    1. Stoll, Michael ; Volz, Sebastian ; Maurer, Daniel ; Bruhn, Andrés: A Time-Efficient Optimisation Framework for Parameters of Opitical Flow Methods. In: Jenssen, R. ; Sharma, P. ; Bianchi, F. M. ; Jenssen, R. ; Sharma, P. ; Bianchi, F. M. (Hrsg.) ; Jenssen, R. ; Sharma, P. ; Bianchi, F. M. (Hrsg.): Proceedings of Scandinavian Conference on Image Analysis (SCIA). Lecture Notes in Computer Science, Proceedings of Scandinavian Conference on Image Analysis (SCIA). Lecture Notes in Computer Science. Bd. 10269 : Springer, 2017c
    2. Maurer, Daniel ; Stoll, Michael ; Volz, Sebastian ; Gairing, Patrick ; Bruhn, Andrés: A Comparison of Isotropic and Anisotropic Second Order Regularisers for Optical Flow. In: Dahl, A.-B. ; Dong, Y. ; Lauze, F. ; Dahl, A.-B. ; Dong, Y. ; Lauze, F. (Hrsg.) ; Dahl, A.-B. ; Dong, Y. ; Lauze, F. (Hrsg.): Proceedings of International Conference on Scale Space and Variational Methods in Computer Vision (SSVM). Lecture Notes in Computer Science, Proceedings of International Conference on Scale Space and Variational Methods in Computer Vision (SSVM). Lecture Notes in Computer Science. Bd. 10302 : Springer, 2017c
    3. Maurer, Daniel ; Bruhn, Andrés ; Stoll, Michael: Order-Adaptive and Illumination-Aware Variational Optical Flow Refinement. In: Proceedings of the British Machine Vision Conference (BMVC), Proceedings of the British Machine Vision Conference (BMVC) : BMVA Press, 2017a
    4. Stoll, Michael ; Maurer, Daniel ; Volz, Sebastian ; Bruhn, Andrés: Illumination-Aware Large Displacement Optical Flow. In: Hancock, E. ; Pelillo, M. ; Hancock, E. ; Pelillo, M. (Hrsg.) ; Hancock, E. ; Pelillo, M. (Hrsg.): Proceedings of International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR). Lecture Notes in Computer Science, Proceedings of International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR). Lecture Notes in Computer Science : Springer, 2017b
    5. Maurer, Daniel ; Stoll, Michael ; Bruhn, Andrés: Order-Adaptive Regularisation for Variational Optical Flow: Global, Local and in Between. In: Dahl, A.-B. ; Dong, Y. ; Lauze, F. ; Dahl, A.-B. ; Dong, Y. ; Lauze, F. (Hrsg.) ; Dahl, A.-B. ; Dong, Y. ; Lauze, F. (Hrsg.): Proceedings of International Conference on Scale Space and Variational Methods in Computer Vision (SSVM). Lecture Notes in Computer Science, Proceedings of International Conference on Scale Space and Variational Methods in Computer Vision (SSVM). Lecture Notes in Computer Science. Bd. 10302 : Springer, 2017b
    6. Stoll, Michael ; Maurer, Daniel ; Bruhn, Andrés: Variational Large Displacement Optical Flow without Feature Matches. In: Hancock, E. ; Pelillo, M. ; Hancock, E. ; Pelillo, M. (Hrsg.) ; Hancock, E. ; Pelillo, M. (Hrsg.): Proceedings of International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR), Proceedings of International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR) : Springer, 2017a
  2. 2016

    1. Maurer, Daniel ; Ju, Yong-Chul ; Breuß, Michael ; Bruhn, Andrés: Combining shape from shading and stereo: a variational approach for the joint estimation of depth, illumination and albedo. In: Proceedings of the British Machine Vision Conference (BMVC), Proceedings of the British Machine Vision Conference (BMVC) : BMVA Press, 2016
    2. Ju, Yong-Chul ; Maurer, Daniel ; Breuß, Michael ; Bruhn, Andrés: Direct Variational Perspective Shape from Shading with Cartesian Depth Parametrisation. In: Breuß, M. ; Maragos, P. ; Wuhrer, S. ; Breuß, M. ; Maragos, P. ; Wuhrer, S. (Hrsg.) ; Breuß, M. ; Maragos, P. ; Wuhrer, S. (Hrsg.): Perspectives on Shape From Shading. Mathematics and Visualization, Perspectives on Shape From Shading. Mathematics and Visualization : Springer, 2016
  3. 2015

    1. Maurer, Daniel ; Ju, Yong-Chul ; Breuß, Michael ; Bruhn, Andrés: An Efficient Linearisation Approach for Variational Perspective Shape from Shading. In: Gall, J. ; Gehler, P. ; Leibe, B. ; Gall, J. ; Gehler, P. ; Leibe, B. (Hrsg.) ; Gall, J. ; Gehler, P. ; Leibe, B. (Hrsg.): German Conference on Pattern Recognition (GCPR 2015). Lecture Notes in Computer Science, German Conference on Pattern Recognition (GCPR 2015). Lecture Notes in Computer Science. Bd. 9358 : Springer, 2015