CSC 487/2503, Fall 2008
Foundations of Computer Vision

General Information

Instructors Prof. Allan Jepson
Email jepson at cs dot utoronto dot ca
Office Hour Thurs. 3-4pm, D.L. Pratt 283D
Or by appointment.
Lectures FALL 2008 Thurs. 1-3, Bahen, Room B024 Lectures start Sept. 11.
Tutorials FALL 2008 Mon. 12-1, Bahen B024. No tutorial on Monday Sept. 8, tutorials start Sept. 15.
Course Information Sheet Handout
Course Bulletin Board https://csc.cdf.toronto.edu/bb/YaBB.pl
Email-Newsgroup Policy There may be no response from 24 hours before an assignment is due, up to the actual time it is due.
Final Exam See the exam timetable for the time, date and place.

Marking

4 Assignments 60%  
Final Exam 40% Previous years' exams

Late Policy

Assignments are due at the beginning of the tutorial or lecture on the due date (i.e. Mon. at 12:10, or Thurs. at 1:10).

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.

Assignments

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. Then, if you wish to set up your home machine, see the matlab/README file unpacked from the matlabVisTools.zip file (see below).


Assignment
Description		 Percent Posting Date Due Date Links
Asgn #1
(revised 7:35pm Sept. 18) 		15% Sept.18 12:10pm, Oct. 6
at tutorial. 		A1handout.zip
utvisToolbox bug fix
Asgn #2
15% Oct. 6 12:10pm, Oct. 27 A2handout.zip
Asgn #3 15% Oct. 26 12:10pm, Nov. 10
(at the beginning of the tutorial) 		A3Handout.zip Contains starter Matlab code and test images.
If you are running Matlab version 6, use the following *.mat files:
trainSet6.mat
testSet6.mat
Asgn #4 15% Nov. 14   1:10pm, Dec. 4
(at the beginning of the lecture) 		The Matlab handout code pigeonTrack.zip (revised Nov. 19, 11am)
The image sequence is at pigeon.zip. DO NOT DOWNLOAD the image sequence to CDF. The sequence is already on CDF in /u/jepson/pub/pigeon/.

CDF Information

By registering in this course you should have a CDF account. For information on CDF see http://www.cdf.toronto.edu/. Before going to a CDF lab, or to the course bulletin board, you need to look-up your CDF account.

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, and also on CS-Lab. After logging onto a CDF (or CS-Lab) 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.

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 matlabVisTools.zip file (60MB). After unzipping this file, see the matlab/README file for instructions on how to set your matlab path. A second zip file containing two image sequences is needed for the motion tutorial, namely matlabVisToolsSeq.zip file (75MB). Unpack this zip file in the same directory as the previous one. It should form a new subdirectory matlab/images/seq/.

Date Topic Matlab Tutorial
Sept. 11, 08 Lecture Notes: Suggested Readings: Getting started with images in Matlab: See the introImageTutorial.m in the ISE toolbox
(See above for directions to ISE)
Extra material: Matlab M-files for Phong shading: phongDemo.m phongShade.m
The generated images: ambient light, metal spheres, shiny spheres, matte spheres
Notes on Phong shading and the peppersc.jpg image discussed there:
Sept. 15 Tutorial Notes:  
Sept. 18 & 25 Lecture Notes: Suggested Readings:
UTVIS: colourTutorial.m
ISE: linSysTutorial.m, samplingTutorial.m, imageTutorial.m
(See above for directions to UTVIS and ISE toolboxes)
Matlab demo: upSample.zip
Oct. 2 Lecture Notes:
Matlab Tutorials:
  • ISE: pyramidTutorial.m
  • UTVIS: cannyTutorial.m
Oct. 9 Robust Estimation
See the following m-files in utvisToolbox/tutorials/lineTut/
  • oTensorDemo.m
  • houghDemo.m
  • robustDemo.m
  • robustLineScript.m
To run these, set your matlab path to include: 		 
 
 addpath([matlabVisRoot '/utvisToolbox/edge']);
 addpath([matlabVisRoot '/utvisToolbox/tutorials/lineTut']);
 addpath([matlabVisRoot '/utvisToolbox/tutorials/lineTut/localUtil']);
Oct. 16 Optical Flow Lecture Notes
Optical Flow Book Chapter
Lecture Notes on Mixture Models
See the following m-files in utvisToolbox/tutorials/motionTut/
  • introMotionTut.m
  • motionTutorial.m
 
Oct. 23 View Based Models
See the following m-files in utvisToolbox/tutorials/eigenTut/
  • trainEigenEyes.m
  • detectEigenEyes.m
 
Oct. 30 Local image features.
Epipolar geometry.
See the following m-files in utvisToolbox/tutorials/
  • SIFTtutorial/tutorial.m
  • 3Drecon/grappleFmatrix.m (update grapple.zip)
 
 
 
Nov. 6 Lecture notes for multiframe factorization.

The lecture and the Matlab tutorial are based on:
  1. Provably-Convergent Iterative Methods for Projective Structure from Motion, S. Mahamud, M. Hebert, Y. Omori and J. Ponce, CVPR 2001.
  2. Self-calibration and metric reconstruction in spite of varying and unknown intrinsic camera parameters, Polleyfeys, Koch and van Gool, IJCV 1999.
UTVIS: Orthographic Factorization and Projective Factorization Demos in tutorials/3Drecon/orthographic/ and tutorials/3Drecon/projective/.
Nov. 13 Tracking.

Nov. 20 Notes on Image Segmentation.
Paco Estrada's pdf notes.
     
Nov. 27 Object Recognition.
  
Dec. 6 Exam Review