Modern Methods in Image Analysis

Winter Term 2008/2009


Modern Methods in Image Analysis

Dr. Andrés Bruhn, Prof. Joachim Weickert

(bruhn@mia.uni-saarland.de)

Winter Term 2008/2009

Seminar (2h)

Important DatesDescriptionAdministrative detailsRequirementsOverview of Topics


First meeting: Friday, July 11, 2008, 14:15h, Bld. E1.1, room 306

Sign-up deadline: Thursday, July 10, 2008.
No free capacity is left in this seminar.

Regular meetings during winter term 2008/2009:
Tuesdays, 16:15h , Bld. E1.1, room 306

Date of first regular meeting: Tuesday, November 25.

Please direct all organisatorial requests to Dr. Andrés Bruhn.


Contents: There has been enormous progress in image processing and computer vision in recent years. Both the quality of the models and the efficiency of the algorithms have improved significantly. In this seminar the participants learn more about such modern techniques that make use of sophisticated strategies. The topics include but are not limited to

  • optic flow

  • stereo reconstruction

  • shape from shading

  • dynamic textures

  • image denoising

Prerequisites: The seminar is designed for graduate students (i.e. advanced Bachelor, Master, and post-Vordiplom) of visual computing, computer science or mathematics. Specific knowledge in image analysis or computer visision is recommended.

Language: Understanding scientific text in English is indispensable. Talks and write-up can be in English or German.


Sign-up: If you are interested to participate, please sign up by e-mailing to bruhn@mia.uni-saarland.de not later than Thursday, July 10, 2008. Please include your name, student ID (Matrikelnummer), date of birth, study program, and valid e-mail address.
Since the number of talks is limited, we ask for your understanding that participants are considered strictly in the order of incoming e-mails – no exceptions.

Sessions: First meeting takes place Friday, July 11, 2008, 14:15h, Bld. E1.1, room 306. Regular sessions will be weekly during the winter term. Exact schedule to be determined at first meeting.


Regular attendance: It is expected that you attend all seminar meetings, except for provable important reasons (we check).

Talk: Talk duration is 30 min, plus 15 min for discussion. Please do not deviate significantly from this time schedule.
You may give a presentation using a data projector (»beamer«), overhead projector or blackboard, or mix these media appropriately. English is preferred as language of presentation; if you should decide to talk in German anyway, you must use slides in English.

Write-up: The write-up has to be handed in till the end of the semester A concrete data will be announced at the first regular seminar meeting. The write-up should summarise your talk, so some 5+ pages per speaker will be adequate in most cases. Electronic submission is preferred. File format for electronic submissions is PDF – text processor files (like .doc) are not acceptable. We recommend using LaTeX. Adhere to the standards of scientific referencing: Quotations and copied material (such as images) must be clearly marked as such, and a bibliography is required.

Mandatory consultation: Talk preparation has to be presented to your seminar supervisor not later than in the week before the talk is given. It's your responsibility to approach us timely and make your appointment!


Please note that the presentation dates are preliminary and subject to change.

No. Topic Date      
1 A1 - Optic Flow and Parameterized Motion
A3 - Optic Flow and Segmentation
Nov 25
2 A4 - Optic Flow and Real-Time Numerics
D1 - Optic Flow and Dynamic Textures
Dez 2
3 B1 - Registration of Tensor Fields
B2 - Registration with Joint Intensity Priors
Dez 9
4 C1 - Stereo and Occlusion Handling
C2 - Stereo and Fundamental Matrix Estimation
Dez 16
5 C3 - Stereo and Scene Flow
C4 - Stereo and Range Images
Jan 13
6 F1 - Shape from Shading
G2 - Denoising with Bilateral Filter
Jan 20
7 G1 - Denoising with Non-Local Means
G3 - Denoising with Unified Smoothing Approach
Jan 27



A1 T. Nir, A. Bruckstein, R. Kimmel
Over-Parameterized Variational Optical Flow
International Journal of Computer Vision (IJCV), 2008
A3 T. Brox, A. Bruhn, J. Weickert
Variational Motion Segmentation with Level Sets
European Conference on Computer Vision (ECCV), 2006
A4 A. Bruhn, J. Weickert
Towards Ultimate Motion Estimation:
Combining Highest Accuracy with Real-Time Performance
International Conference on Computer Vision (ICCV), 2005
D1 T. Amiaz, S. Fazekas, D. Chetverikov, N. Kiryati
Detecting Regions of Dynamic Texture
International Conference on Scale Space and Variational Methods in Computer Vision (SSVM), 2007
B1 S. Barbieri, M. Welk, J. Weickert
Variational Registration of Tensor-Valued Images.
Workshop Tensors in Image Processing and Computer Vision
IEEE Conference on Computer Vision and Patteren Recognition, 2008
B2 D. Cremers, C. Guetter, C. Xu
Nonparametric Priors on the Space of Joint Intensity Distributions for Non-Rigid Multi-Model Image Registration.
IEEE Conference on Computer Vision and Patteren Recognition (CVPR), 2006
C1 R. Ben-Ari, N. Sochen
Variational Stereo Vision with Sharp Discontinuities and Occlusion Handling.
International Conference on Computer Vision (ICCV), 2007
C2 L. Valgaerts, A. Bruhn, J. Weickert
A Variational Approach for the Joint Recovery of the Optical Flow and the Fundamental Matrix.
Annual German Pattern Recognition Symposium (DAGM), 2008
C3 F. Huguet, F. Devernay
A Variational Method for Scene Flow Estimation from Stereo Sequences.
International Conference on Computer Vision (ICCV), 2007
C4 C. Zach, T. Pock, H. Bischof
A Globally Optimal Algorithm for Robust TV-L1 Range Image Integration.
International Conference on Computer Vision (ICCV), 2007.
F1 O. Vogel, A. Bruhn, J. Weickert, S. Didas
Direct Shape-from-Shading with Adaptive Higher Order Regularisation.
International Conference on Scale Space and Variational Methods in Computer Vision (SSVM), 2007
G2 C. Tomasi, R. Manduchi
Bilateral Filtering for Gray and Color Images.
International Conference on Computer Vision (ICCV), 1998.
G1 A. Buades, B. Coll, J.-M. Morel
A Non-Local Algorithm for Image Denoising.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2005.
G3 P. Mrázek, J. Weickert, A. Bruhn
On Robust Estimation and Smoothing with Spatial and Tonal Kernels.
Geometric Properties from Incomplete Data, 2006.


Andrés Bruhn / July 4, 2008

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