Image Canons 2010-2011
Course Description
The purpose of the study group is to go through the most important
(canonical) papers in Image Analysis and Pattern Recognitions to
broaden the education of PhD students of the Image Group at the
Department of Computer Science, University of Copenhagen. For that
purpose, after discussion with the senior members of the Image Group,
21 papers have been selected, covering a broad spectrum in Image
Analysis, and being some of the most cited in the field, as well as of
particular importance for the research performed at the Image
Group. Part of this list may be subject to changes after discussion
with the groups more senior staff.
The course will consist in 1h
weekly discussions around one of the selected papers. To that purpose,
all the enrolled student will read the selected paper prior to
discussion, while one of them will present it in details to the
audience. A VIP with deeper knowledge of the paper and techniques
involved will lead the discussion.
PhD students from other
groups as well as non PhD students are welcome too.
Exam form
It's a Pass/not Passed, 5 ECTS. Each student must present ast least two papers from
the list and follows the other sessions on a (very) regular basis in order to pass
(bringing cake is not mandatory).
Registration
So far, just send a mail to François Lauze: francois@diku.dk
Schedule
Mondays 10h-11h (can last a bit longer...)
Place: Mødelokalet B, DIKU
Hansen and Yu was manned, thanks Aasa! And the happy winners are
Potentially very useful!
A paper on how to read a paper has been added to the extra materials!
Participants
- Senior speakers
- François Lauze
- Søren Hauberg (yes, doule role this year)
- Sune Darkner
- Aasa Feragen
- Christian Igel
- Junior participants
The selected papers are the following (some
small modifications are not excluded)
- D. Mumford. Bayesian Rationale for
the Variational Formulation. In Geometry-Driven Diffusion In Computer
Vision, pages 135-146. Kluwer Academic Publishers, 1994. Computational Imaging
And Vision.
- S. Geman and D. Geman. Stochastic
Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 6(6): 721-741,
1984.
- T. F. Cootes, C. Taylor, D. Cooper, and
J. Graham. Active Shape Models-their
Training and Application. Computer Vision and Image Understanding,
61(1):38-59, 1995.
- S. Kichenassamy, A. Kumar, P. J Olver, A. Tannenbaum,
A. Yezzi. Conformal
curvature flows: From phase transitions to active vision toghether with
V. Caselles, R. Kimmel, and
G. Sapiro. Geodesic Active
Contours. The International Journal of Computer Vision, 22(1): 61-79,
1997.
They were proposed simultaneously.
- T. F. Cootes, G. J. Edwards, and
C. J. Taylor. Active Appearance
Models. IEEE Transactions on Pattern Analysis and Machine Intelligence,
23(6): 681-685, 2001.
- M. H. Hansen and B. Yu. Model Selection
and the Principle of Minimum Description Length. Journal of the American
Statistical Association, 96(454): 746-774, 2001.
- B. K. Horn and
B. G. Schunck. Determining
Optical Flow. Artificial Intelligence, 17: 185--203, 1981.
- A. Verri and T. Poggio,
Motion Field and Optical Flow: Qualitative Properties. IEEE Trans. on
Pattern Analysis and Machine Intelligence, 11(5): 490-498, 1989.
- C. Tomasi and T. Kanade, Shape and
Motion From Image Streams under Orthography: A Factorization Method.
The
International Journal of Computer Vision, 9(2): 137-154, 1992.
- M. Isard and A. Blake. CONDENSATION -
Conditional Density Propagation for Visual Tracking. The International
Journal of Computer Vision, 29(1): 5-28, 1998.
- A. K. Jain, R. Duin, and
J. Mao. Statistical Pattern
Recognition: a Review. IEEE Trans. on Pattern Analysis and Machine
Intelligence, 22(1): 4--38, 2000.
- J. J. Koenderink. The Structure of
Images. Biological Cybernetics, 50: 35-41, 1984.
- T. Lindeberg. Feature Detection
With Automatic Scale Selection. The International Journal of Computer
Vision, 30(2): 77-116, 1998.
- P. Perona and J. Malik. Scale-Space
and Edge Detection Using Anisotropic Diffusion. IEEE Transactions on
Pattern Analysis and Machine Intelligence, 12(7): 629-639, July 1990.
- D. Rueckert, L. I. Sonoda, C. Hayes, D. L. G. Hills, M. O. Leach, and D. J. Hawkes.
Nonrigid Registration Using
Free-Form Deformation: Application to Breast MR Images. IEEE Transactions
on Medical Imaging, 18(8): 712-721, 1999.
- P. Viola and W. M. Wells III. Alignment
by Maximization of Mutual Information. The International Journal of
Computer Vision, 24(2): 137-154, 1997.
- S. C. Zhu, Y. Wu, and D. Mumford. Filters,
Random Fields and Maximum Entropy (FRAME).
The International Journal of Computer Vision, 27(2): 1-20, 1998.
- T. Chan and J. Shen. Mathematical Models
for Local Nontexture Inpainting. SIAM journal of appl. Math, 62(3):
1019-1043, 2002.
- C. Cortes and
V. Vapnik. Support-Vector
Networks Machine Learning, 20: 273-297, 1995
- M. Belkin and
P. Niyogy Laplacian Eigenmaps
for Dimensionality Reduction and Data Representation Neural Computations
15: 1373-1396, 2003
About this page
This page is maintained by Chen Chen
and François Lauze. For any question, suggestion... please contact us at:
- chen at diku dot dk
- francois at diku dot dk
Last update: April 11th 2011.
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