CSC 320, Spring 2005
Introduction to Visual Computing

General Information

Instructors Prof. Allan Jepson
Email jepson at cs dot utoronto dot ca
Office Hour Mon. 1-3pm, D.L. Pratt 283D
Or by appointment.
Lectures Spring 2005 Mon. and Wed. 9-10, Room BA 1200
Tutorials Spring 2005 Tutorial 9am, Fri, Jan 21 in BA 1200
Text None
Course Newsgroup Read the CSC320 Newsgroup
Post a message to the course newsgroup.
Email-Newsgroup Policy There may be no response from 24 hours before an assignment is due, up to the actual time it is due.


4 Assignments 40%
Final Exam 60%

Late Policy

Assignments are due at the beginning of the tutorial or lecture on the due date (i.e. Mon./Wed./Fri at 9:10).

The penalties for lateness are:

Hard copies of late assignments should be handed into the AI Office, Pratt 283, during business hours. The date and time should be marked, and it needs to be signed for by someone in the office.

Check your current marks on-line. So far we only have A1 marked.


Links to assignments and related information are provided here.

If you are new to Matlab, first read the Matlab primer and try running the code described there at the CDF-PC lab.
Percent Posting Date Due Date Links
Asgn #1 10% Jan. 25 Feb. 9 checkerAliasHandout.m
Electronic submit instructions
A1 Written Solutions
A1 Soln Matlab code (zip file)
Asgn #2 10% Feb. 9 Mar. 2 Beier and Neely paper on Image Morphing Matlab starter code
Electronic submit instructions
A2 Written Soln (pdf file)
A2 Soln Matlab code (zip file)
Asgn #3 10% Mar. 9 Mar. 23 Litwinowicz's paper on painterly rendering Matlab starter code
Electronic submit instructions
Asgn #4 10% Mar. 29 Apr. 8 Test images
Electronic submit instructions
A4 Soln Matlab code (script file)

Lecture and Tutorial Materials

Links to some of the lecture/tutorial notes are provided below.

Matlab tutorials are also provided to illustrate many of the concepts introduced in this course. The tutorials are installed on the CDF lab machines. After logging onto a CDF machine, cd ~jepson/pub/matlab and read the README file. This file tells you how to set up matlab so that it will run the tutorials. The tutorials are located in two directories:

We indicate which toolbox to look in below.

Optional: The Matlab toolboxes we use in this course are also available for download to your home computer (assuming you have Matlab at home) from the file (51MB). After unzipping this file, see the matlab/README file for instructions on how to set your matlab path. However, you do NOT need to have Matlab at home, since the software is available in the CDF Lab.

Date Topic Links
Jan. 5 and 10 Linear Systems and Convolution
Notes on linear systems.
ISE: introImageTutorial.m, linSysTutorial.m
(See above for directions to ISE)
Jan. 12 Fourier Analysis
Notes on Fourier analysis.
ISE: imageTutorial.m, linSysTutorial.m
(See above for directions to ISE)
Jan. 14
Intro to Matlab

Jan. 17 Application of Fourier Analysis:
1D Signal Interpolation.
Matlab upSample zip file
Jan. 21

Jan. 28
Sampling Theorem ISE: samplingTutorial.m
Jan. 31 Sampling Theorem
Lecture notes on sampling.
ISE: samplingTutorial.m
Feb. 2 2D Image Interpolation Lecture notes ISE: imageTutorial.m
Feb. 4
Image Operatons in Matlab ISE: imageTutorial.m
Feb. 7 2D Fourier Transforms
Lecture notes on 2D Fourier transforms and filters.
ISE: imageTutorial.m Matlab 2d Fft and sampling demo.
Feb. 9 Image Morphing the paper and Matlab handout code for Asgn #2 above.
Feb. 21 and 23 Colour
Lecture notes on colour.
UTVIS: colourTutorial.m
Mar. 2 Lecture notes on 1D edge detection.
Mar. 8 Lecture notes on image edge detection. UTVIS: cannyTutorial.m
Mar. 11
Tutorial notes on Canny edge detection. UTVIS: cannyTutorial.m
Mar. 14 and 16 Lecture notes on image pyramids. ISE: pyramidTutorial.m (first 200 lines)
Mar. 21 and 23 Lecture notes on regularization.
Mar. 28 to Apr. 4 Lecture notes on robust regularization. Matlab demo for 1D robust estimation