CS 4330: Computer Vision

Synopsis

This course provides an overview of Computer Vision - enabling computers to understand visual input. The course introduces the major concepts and methods, and gives the student a sample of problem settings and techniques for solving them. It is intended for the student who wants to get an understanding of how computer vision works and how it can perform such diverse tasks as object recognition, robot navigation, and increase situational awareness. The course will have strong ties between theory, examples of its application, and practical exercises in order to promote fast and persistent learning.

Announcements and Homework Assignments

Web and data space

http://www.movesinstitute.org/~kolsch/courses/CS4330/CS4330.html
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Grades for homeworks etc will be on Blackboard.

Hours

Monday 1500-1650, WA-275
Wednesday 1500-1750, WA-275
These two time slots will be used for lectures and/or lab time. Please bring your laptop for every meeting.
Final: Tuesday 12/13/05, 1300-1450 WA-275

Office Hours

I am available for questions and help whenever I am in my office (WA-275) and have some time. If you would like a firm appointment, please don't hesitate to set one up by email.

Textbook

D. A. Forsyth, J. Ponce; Computer Vision: A Modern Approach (Prentice Hall)
Since I was asked: there are no color pictures in this book. Sniff.

Grading

50% homework assignments, quizzes (if any)
30% programming project (Matlab or OpenCV)
20% final

Equipment

All special equipment and software will be provided to you:
Matlab with Image Processing Toolbox, USB or FireWire (1394) camera, OpenCV

Programming Project

As part of the course, you will complete a small programming project with the help of a high-level computer vision library (OpenCV) to demonstrate some of the methods you have learned in class. Sample projects are:

Syllabus

Syllabus

Resources