CS651: Computer Vision
Spring 2007
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Course Summary
Lectures: T,Th 11:00-12:15, Room: MEC 345
Instructor: Jason Lawrence - 212 Olsson (office hours: Wed. 3-5 & by appointment)
Announcements
Assignment 4 has been posted.
Start forming groups of 2-3 for the final project.
Course Description
This course serves as an introduction to 2-D and 3-D computer vision.
Topics include: principles of image formation; edge and feature
detection; segmentation and clustering; feature recognition; feature
tracking and optical flow; camera calibration; stereo-based scene
reconstruction; photometric stereo; and image-based rendering and
modeling.
Prerequisites
The only prerequisite is CS216. This course will require programming
(in C, C++, and/or Matlab), as well as some background in data
structures and linear algebra. Experience with signal processing,
statistics, and/or computer graphics is useful but not necessary.
Textbook
Introductory Techniques for 3-D Computer Vision by Emanuele
Trucco and Alessandro Verri. We will also read a few research papers.
Grading
There will be four programming assignments each worth 17.5% of your
grade and a final project worth 30%.