CS498Q/698Q -- Computational Vision

Important Notes:

Marks Posted / Projects Returned: Marks and projects are available outside my office (DC2510). Feel free to see me if you have questions or grading concerns.

Project: Brief (one paragraph) proposal due Tues 27 Feb. If you require help selecting a project, please contact me. If you can't decide on a project, consider implementing some of the algorithm(s) discussed in class (eg., Optical flow, Factorization method for structure from motion, etc). I can provide you with sample data.

Running Matlab: Make sure you are running Matlab version 5.x. (eg., on picard.math and other machines). Some machines may have older versions of Matlab (4.x) which do not work.

Administrivia:

Time: Winter 2001; Lectures TR 1:00-2:30, Tues MC2036, Thurs MC4042; Tutorial F 2:30-3:30 MC4062; Office hour TBA. Note: Tutorials will be given only when necessary (eg., help with assignments). Dates will be announced in class.

Instructor: Richard Mann, DC2510, x3006, mannr@uwaterloo.ca, http://www.cs.uwatleroo.ca/~mannr

For more info, see CS498Q from Winter 2000.

Objectives: The objective of this course is to provide a self-contained treatment of some fundamental problems and solutions in computational vision. It will also provide exposure to current research issues to prepare students for further studies (advanced level courses and/or graduate studies) in vision.

Prerequisites: There are no formal prerequisites for this course, however, it is advisable to have some exposure to numerical computation, especially linear algebra (eg., CS370), and some basic programming experience. Programming will be done in C and Matlab.

References: All required material will be provided in lectures. The following recommended books will be on reserve in the library:

Grading (tentative): The lecture material will be same for undergrad and grad students. The grading will be: three or four assignments (60%), Project (40%). The project could include a literature review, an experimental analysis of some algorithm, an implementation of a new algorithm, or any other topic of mutual interest to the student and instructor. Graduate students will be given additional questions on the assignments and/or will be required to undertake a larger project.

General Information:

Assigments:

Lectures:

Reference material:

Course software:

Project ideas:

Additional References (not required for course):

  • The following resources are from Allan Jepson's computer vision course at University of Toronto. These are not required for this course, but you might find them useful.
  • CMU course on Image-based representation and rendering. This page has a very good set of resources about warping, image compositing, structure from motion, etc.
  • Review of projective geometry (Appendix from a book by Zisserman and Mundy.) Please let me know if you get through this. I got stuck near the beginning.
  • Wearcam Steve Mann's webpage on wearable computers and cameras.
  • Gerhard Roth (NRC) Software for 3D scene reconstruction (uses Epipolar geometry). Also, some tutorials on reconstruction using projective geometry.