Welcome to CS 223-B: Introduction to Computer Vision, Winter of 2004
This course was taught in the Winter Quarter of 2004. It is part of an annual series, so check out the latest course info
This course will cover the essentials of
computer vision. It is a graduate-level course of interest to anyone
seeking to process image or camera information, or to acquire a
general background in issues related to real-world perception and
The course involves three types of activities:
Interactive classroom sessions, where students together with the
instructor explore the basic
mathematical foundations behind a range of popular
algorithms. Some of the sessions will take the form of
traditional-style teaching, whereas others will be dedicated to
brainstorming on challenging open problems.
Homework assignments will provide an opportunity to deepen the problem
solving skills acquired in class.
A major research-style programming assignment that seeks to enable students to develop computer vision software, while deepening their understanding of the relation of
mathematical calculus and the "real world."
This is an introductory graduate level
course. Familiarity with
basic statistical concepts (Bayes rule, PDFs, projective geometry, Kalman filters, continuous
distributions...) will be helpful for this course, as will be hands-on
experience with software development in C or C++ and Matlab. Intro
tutorials will be given in Matlab and in the vision library OpenCV. But the most important
prerequisite will be creativity and enthusiasm.