COMP-558 Fall 2008-2009: Fundamentals of Computer Vision
Schedule
Instructor:
Kaleem Siddiqi
Schedule: Tuesday/Thursday, 16:05 pm. - 17:25 pm.
Class Room: ENGTR 0060
Office: ENGMC 420
Office Hrs: Thursday, 9:00 am. - 10:00 am. (or by appt.)
E-mail: siddiqi "at" cim "dot" mcgill "dot" ca
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TA:
Maxime Boucher
Office Hrs: W: 1:00 pm. - 3:00 pm, TR 3106.
E-mail: maxime.boucher "at" mcgill "dot" ca
Maxime's
COMP 558 web page .
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Overview
Computer vision involves the development of machine algorithms which
have the potential to mimic a biological organism's ability to
``see''. Though the sense of vision is immediate for most people, the
complexity of the task that the human visual system accomplishes is
enormous. In general, the inference of properties of the three-dimensional
world from two-dimensional images is very challenging.
Nevertheless, this has been a rich area for investigation for the past
several years. To date the field has advanced to the point where a
core of algorithms and techniques have been developed for specific
visual tasks in constrained settings, with a solid mathematical
foundation. Several international research laboratories now exist and
applications of computer vision techniques in industry, robotics, and
bio-medicine abound. This course seeks to present the fundamentals of
computer vision at an advanced undergraduate/beginning graduate level.
The mathematical background for the course includes calculus and
linear algebra. Fundamentals of other areas, such as linear systems
and partial differential equations, will be covered as necessary. It
will also be assumed that students have practical experience with
programming in a Unix environment using C, as well as a solid
theoretical grasp of computer science algorithms and data
structures. This computer science background will be necessary to
carry out assignments and projects which involve the design and
implementation of computer vision techniques.
News
Content
The course will cover a number of topics ranging from low level to
high level vision, with a focus on both the mathematical formulation
of vision tasks, and the development and implementation of algorithms
to solve them. Lecture topics, subject to revision, are listed below.
Student prepared course notes
The following is a list of student prepared course notes, summarizing
aspects of the material presented in class, or in reference
material and texts. It is provided here, in uneditted form.
Useful Links
Prerequisites
Text Books
Evaluation
Student Guide to Avoid Plagiarism
Sample past Student Projects
The following are links to some of the final projects
from a previous year, in cases students made their presentations
or material available over the web.