Computer Science 159.731 Course Outline, Semester 1 - 2008


Introduction

This paper is an advanced course in Machine Vision. For the purpose of this course, we will take machine vision to be the study of how a computer can be made to perceive the world using data acquired from an imaging device. Computer vision is an exciting area where challenging problems must be solved.

Assessment

The course will be assessed by a combination of practical and theoretical work. There will be no formal lectures because of the small class size, but there will be tutorials and seminars. Each week we will discuss a different aspect of machine vision. You will be given selected papers to read and the tutorials will be based on this reading. You should keep a reading journal, with rough notes about everything you have read and comments. This will be marked at the end of the semester. There will be 3 programming assignments, a seminar paper and two exams.



Reading Notes

10%

Assignments (3)

30%

Seminar

15%

Mid Semester Test

15%

Exam

30%





Course Schedule

This is a rough plan, the course may not conform to this schedule.

1 - The Human Visual System
This is an example of a working vision system. We will try to find out how it works.
2 - Low Level Vision
Image acquisition and simple neighbourhood operations.
3 - Basic Pattern Recognition
The pattern space and classification methods.

4 - 3D Vision
Shape from X
5 - Frequency Domain Methods
The 2D FFT and its uses. Other Transforms
6 - Moving Images
Optical flow
7- High Level Vision
Models of the world
.



 M Johnson 2003