CS 482: Computer Vision

Wednesday, 4:30 pm - 7:10 pm, in Robinson Hall B104

Zoran Duric
http://cs.gmu.edu/~zduric/

Data structures
Linear algebra and calculus
A good working knowledge of C/C++ or Java or Python programming

Grading will be based on a combination of the following factors:
Class attendance and participation 10%.
Homeworks and projects 50% (about every 2 weeks).
A midterm 20%.
A final 20%.

You have 10 late dates that you can distribute among your assignments. After those late days are used up there will be 100% penalty on any late assignment. You are responsible for keeping track of the late days used. I will have the record and you can check with me to find out where you stand.

Computer Vision: Algorithms and Applications. R. Szeliski, Springer, 2010, required, Online version of the book can be found at http://szeliski.org/Book/
Computer and Machine Vision: Theory, Algorithms, Practicalities, E.R. Davies, Academic Press, 2012, recommended , A lot of well-explained algorithms with implementation details
Computer Vision, G. Stockman and L. Shapiro, Prentice-Hall, 2001, recommended
Computer Vision: A Modern Approach: D. Forsythe and J. Ponce, Prentice-Hall, 2003, recommended
Image Processing, Analysis, and Machine Vision. Sonka, Hlavac, and Boyle. Thomson, recommended

The class enforces the GMU Honor Code (see http://oai.gmu.edu/honorcode/), and to the more specific honor code policy special to the Department of Computer Science (see http://cs.gmu.edu/wiki/pmwiki.php/HonorCode/CSHonorCodePolicies). You will be expected to adhere to this code and policy.

If you heve a documented learning disability or other condition which may affect academic performance, make sure this documentation is on file with the Office of Disability Services and come talk to me about accommodations.

Basic knowledge of image formation process
Basic knowledge of image processing techniques for color and gray level images: edge detection, corner detection, segmentation
Basics of video processing, motion computation and 3D vision and geometry
Ability to implement basic vision algorithms in Matlab and use OpenCV (open source computer vision library)
Ability to apply the appropriate technique to a problem, write a project report and present the results in class.