Seminar:
CSE 741 Fall 2007
Current Problems in Computer Vision
A. Course objectives and preliminaries
This is the website for my Fall '07 seminar on computer vision.
The purpose of the seminar is to explore (take a guess) current
problems in computer vision: those issues, approaches and applications
evoking notable current research interest and promise. At the end of
the seminar, participants should be aware of trends and directions in
current computer vision research and have explored at least one in some
depth, given a thorough tutorial presentation on it, and written a
report including original research ideas in that domain.
After a few weeks of general survey of selected topics led by the
course director Peter Scott (that's me), each registered student will
select a topic from the list of selected topics (or chosen by
him/herself with my concurrence), and deliver a presentation on that
topic. This website will serve mainly as a repository of files
and links relevant to the course. As student presentations come
available, they will be added.
Enrollment is limited to grad students with at least one previous
course in image processing or computer vision. The group will meet
weekly for one 2 1/2 hour session at a time that fits into everyone's
schedule. On the first day of class for the Fall semester, Monday Sep
28, I will email everyone
who has registered for the course and ask their class and teaching
schedules. I will then send another email around indicating what our
regular meeting time and place for the semester will be. If you are
interested in attending but do not register for the course, please
check my office door (Bell 136), I will post the time and place for our
meetings as soon as this information is available.
I will have office hours this semester 2:30-3:30PM MWR Bell 136 and can
be reached by email at peter@buffalo.edu or phone at 716-645-3180 x
137.
This is the current syllabus, with a useful
introductory reference for each topic linked. Registered students are
asked to review
these references before the class in which they will be surveyed. These
references are just basic tutorial introductions, which give the
flavor of the topic but should not be expected to supply detail and
technical information adequate for a thorough understanding.
1. Image processing from still images
1.1 Segmentation: fast marching http://math.berkeley.edu/%7Esethian/Explanations/fast_marching_explain.html
1.2 Shape recovery: level sets http://math.berkeley.edu/%7Esethian/Explanations/level_set_explain.html
1.3 Segmentation: graph cuts http://www.cis.upenn.edu/~jshi/GraphTutorial/Tutorial-ImageSegmentationGraph-cut1-Shi.pdf
1.4 Registration: rigid vs non-rigid http://www.cs.wright.edu/~agoshtas/CVPR04_Registration_Tutorial.html
1.5 Registration of images with maps Haala_2003.pdf
1.6 JPEG2000 http://stargate.ecn.purdue.edu/~ips/tutorials/j2k/
2. Computer vision from still images
2.1 OR: SVM methods http://www.support-vector.net/icml-tutorial.pdf
2.2 OR: Learning LeCun_2004.pdf
2.3 Free-viewpoint rendering http://iphome.hhi.de/smolic/docs/Smolic_ICIP04_FVV.pdf
2.4 Multi-view 3D reconstruction Vogiatzis_2005.pdf
2.5 Multi-sensor image fusion http://www.ece.lehigh.edu/SPCRL/IF/image_fusion.htm
3. Video processing
3.1 Particle filters for tracking Li_2004.pdf
3.2 MPEG-4/H.264 video coding http://www.m4if.org/resources/IEEESpectrum/mpeg-4.htm
3.3 Model-based tracking http://csdl2.computer.org/comp/proceedings/ismar/2003/2006/00/20060313.pdf
3.4 Tracking using Bayes' nets http://www.cs.ubc.ca/~murphyk/Software/BNT/Talks/BNT_mathworks.ppt
3.5 Free-viewpoint video http://www.merl.com/reports/docs/TR2003-137.pdf
3.6 Motion detection http://lear.inrialpes.fr/people/triggs/events/iccv03/cdrom/iccv03/0734_viola.pdf
3.7 Motion segmentation Weiss_2003.pdf
4. Computer vision from video
4.1 Detecting surprises, abnormalities Koller_2002.pdf
4.2 Modelling, identifying behavior Gong_2002.pdf
4.3 Detecting, tracking people Cutler_2003.pdf
4.4 Wayfinding for the vis impaired Nagarajan_2003.pdf
5. Mathematical foundations
5.1 Representation: wavelets http://www.amara.com/IEEEwave/IEEEwavelet.html
5.2 Superresolution http://cmc.rice.edu/docs/docs/Wag2004Apr5ImageSuper.pdf
5.3 Learning Weng_2000.pdf
5.4 Modelling uncertainty: prob, belief, fuzzy, rough sets, intervals, etc. Smets_1999.pdf
5.5 Evaluation methods Martens_2002.pdf
5.6 Mosaicking Hsieh_2003.pdf
5.7 A contrario detection methods VISTA_2004.pdf
5.8 Belief and image uncertainty Sun_2003.pdf
6. Architectures and hardware
6.1 FPGA architectures http://www.us.design-reuse.com/articles/article10943.html
6.2 Vision on a chip http://www.nasatech.com/Briefs/Feb00/NPO20449.html
6.3 Smart cameras Leeser_2004.pdf
7. Miscellaneous
7.1 Watermarking Perez_200X.pdf
7.2 Image steganography Johnson_1997.pdf
7.3 Inpainting methods http://www.math.ucla.edu/~imagers/htmls/inp.html
8. Topics not discussed (duplicates other courses)
1. No face recognition
2. No image indexing or retrieval
3. No biometrics (eg. fingerprints)
4. No cv for bioinformatics
5. No active or animate vision
Class Schedule
Student presenters and their topics will be filled in as they become
scheduled.
|
Date |
Presenter |
Topic |
Prep Readings |
|
Aug 31 |
|
No meeting |
|
|
Sep 7 |
Peter Scott |
Organizational meeting |
|
|
Sep 14 |
Peter Scott |
Overview of Topics I |
1.1-2.5 |
|
Sep 21 |
Peter Scott |
Overview of Topics II |
1.5-3.7 |
|
Sep 28 |
Peter Scott |
Overview of Topics III |
4.1-7.3 |
|
Oct 5 |
Hung Ho |
||
|
Oct 12 |
Thomas
Tiju |
3.6 Motion detection |
|
|
Oct 19 |
Vincent
Chen |
4.3
Detecting, tracking people |
|
|
Oct 26 |
Omkar
Mehendale |
||
|
Nov 2 |
Damien
Jose |
||
|
Nov 9 |
Prashant
Gokhale |
3.2 MPEG-4 |
|
|
Nov 16 |
|
No class |
|
|
Nov 23 |
Fall Break |
No class |
|
|
Nov 30 |
Siddharth
Jayaraman |