Course Description and Overview

This seminar will survey the state of the art in computer vision through readings of original papers and implementation of selected algorithms. Students will develop their ability to convey technical content in public by taking the lead role in presenting selected individual papers. Each student will implement a significant project over the course of the semester, based upon current published work. Students will take the lead in directing the course of study as needed to support their projects. Prerequisites: CSC 112, MTH 153.

The course will cover some subset of the following list of topics.


You should come out of this course with a sense of the fun, possibilities, and challenges inherent in computer vision. You will learn to read and analyze a computer science research paper, and present its significant results. You may gain some familiarity with Matlab. Finally, you will see the sorts of problems currently under study by researchers in computer vision.

Course Materials

Computer Vision: Algorithms and Applications, by Richard Szeliski. You may buy a physical copy if you wish, or rely on the free PDF version.
Also Recommended
Introduction to MATLAB for Engineers, by William J. Palm III. Free PDF version.
Machine Vision, by Ramesh Jain, Rangachar Kasturi, and Brian G. Schunck. This has good coverage of basic image processing techniques, and has been used as the primary text in the past.
Computer Vision: A Modern Approach, by David A. Forsyth and Jean Ponce. This is a very complete text, but is written at an advanced graduate student level. It has more mathematical detail, and may be useful as a reference. I have a copy that may be loaned out for short periods.
Electronic/On Reserve in Young Library:
Vision : a computational investigation into the human representation and processing of visual information, by David Marr. [Electronic Resource]
The ecological approach to visual perception, by James J. Gibson. [on reserve]
Both of these are older, more philosophical books on vision.

I have additional books on computer vision that may be loaned out for short periods.



Portfolios and participation activity will be reviewed during the semester prior to the assignment of a final grade.

Students may wish to read the instructor's policy on grade averaging.

Collaboration policy: Because the details of each student's project will differ, consultation on technical aspects is permitted. As a guiding principle, any work submitted for grading must accurately reflect the understanding of the student presenting it. Cases where signifigant assistance was provided by others must always be documented clearly. Abuses of this policy will result in a referral to the Honor Board.

Course Details

Nick Howe
Ford Hall 354

Office hours
Meeting Times
2:30-3:50 Mondays and Wednesdays
Ford 345