Computer Vision

CS766, Fall 2010
Time: Tu Th 2:30pm - 3:45pm
Room: COMP S&ST 1325

The goal of computer vision is to compute properties of the three-dimensional world from digital images. Specific problems in this field include reconstructing the 3D shape of an environment, determining how things are moving, and recognizing familiar people and objects and their activities, all through analysis of images and videos.

This course will provide an introduction to computer vision, including such topics as image formation, feature detection, motion estimation, image mosaics, 3D shape reconstruction, and object recognition. Applications of these techniques include building 3D maps, creating virtual characters, organizing photo and video databases, human computer interaction, video surveillance, automatic vehicle navigation, and others.

Prerequisites
This course will be self-contained; students do not need to have computer vision background. Prerequisites are linear algebra, calculus, and C/C++ programming.
If you are not sure whether you can take it, please send me email or talk to me!

Textbooks
Forsyth & Ponce, Computer Vision:  A Modern Approach, Pearson, 2002, ISBN 0130851981

Recommended readings
Richard Szeliski, Computer Vision: Algorithms and Applications (Incomplete draft), 2008.
L. Shapiro and G. Stockman, Computer Vision, Prentice-Hall, Upper Saddle River, N.J., 2000.
R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, Cambridge University Press, Cambridge, UK, 2000.
M. Sonka, V. Hlavac and R. Boyle, Image Processing, Analysis, and Machine Vision, Brooks/Cole Publishing, 1999.
E. Trucco and A. Verri, Introductory Techniques for 3-D Computer Vision, Prentice-Hall, Upper Saddle River, N.J., 1998.
A. Watt and F. Policarpo, The Computer Image, Addison-Wesley, Harlow, UK, 1998.
R. Jain, R. Kasturi and B. G. Schunck, Machine Vision, McGraw-Hill, New York, 1995.
V. S. Nalwa, A Guided Tour of Computer Vision, Addison-Wesley, Reading, Mass., 1993.
O. Faugeras, Three-Dimensional Computer Vision, MIT Press, Cambridge, Mass., 1993.
B. K. P. Horn, Robot Vision, McGraw-Hill, New York, 1986.

Grading
The grade is based on one written assignment (5%), three programming projects (15% each), paper presentation (15%), and a final project (35%). There will be no exams. The final project is research-oriented: students propose their own project topics, subject to the instructor's approval. The final project can be a pure vision project or an application of vision technique in the student's own research area.

Administrative
Email list: compsci766-1-f09@lists.wisc.edu
Computer account: Everyone registered in this class will get a Computer Systems Lab account to do project assignments.