Instructor | Prof. Allan Jepson. |
jepson at cs dot toronto dot edu | |
Office Hour | Fri. Noon-1pm, D.L. Pratt 283D, or by appointment. |
Lectures FALL 2011 | Times: Tues @ 3pm, Fri @ 11am (Note different times on Tues. and Friday), Room: Lash Miller, 80 St. George St., Room 123 Starts: Tues. Sept. 13. |
Tutorials FALL 2009 | Time: Thurs @ 3pm, Room: Lash Miller, Room 123. Start: Thurs. Sept. 15. |
Course Information Sheet |
Handout |
Course Bulletin Board | https://csc.cdf.toronto.edu/bb/YaBB.pl?board=CSC420H1F |
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 | The Faculty of Arts and Science will schedule the exam sometime in October. Look up the time and place on the Examinations page, where it will be listed as CSC420. |
Shortcuts To... | Assignments, Lecture and Tutorial Notes |
2 Assignments | 40% | |
1 Project | 60% |
The penalties for lateness are:
If you are unable to hand in an assignment or write an exam due to a serious medical condition, have your doctor complete a UofT Student Medical Certificate available from UofT Health Services Forms. Submit the completed certificate to your instructor.
Your marks are/will be posted on the CDF secure website
This course will use Matlab. If you are new to Matlab, first read the Matlab primer and try running the code described there.
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:
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/.
We take plagarism very seriously. Everything you hand in to be marked, namely assignments, tests and the final exam, must represent your own work. Read How not to plagarize.
Assignment Description |
Percent | Posting Date | Due Date | Links |
A1 | 20% | Sept. 27 | 3pm, Thurs. Oct 13 | Matlab starter code. |
A2 | 20% | Oct. 18 |
Extended to: 8am, Thurs. Nov. 3 |
Matlab starter code. |
Project (Updated: 4:11pm 09/11/11) | 60% | Nov. 9 |
Proposal: Tues., Nov. 15, 3pm. Milestone Presentation and Report: Fri., Dec. 2, 11am. Final Report: Wed., Dec. 7, 3pm (extendable). |
NEW (5pm Nov.18): Matlab starter code. Image sequence on CDF: /u/jepson/pub/csc420/data/Flowers_03[p].avi Here Flowers_03p.avi is just the first 50 or so frames. See VLFeat.org for info on the VLFeat software. |
Links to some of the lecture/tutorial notes
are provided below.
Date, Type
Lecture/Tutorial Notes
Additional/Optional Readings
Sept. 13-16
Lecture Notes
Image Projection
Optional Reading: Section 2.1 of Szeliski's text.
Sept. 15
Tutorial Material
Intro to Matlab
Geometrical Review of Linear Algebra
Sept. 20-23
Lecture Notes
Linear Filtering
Required Reading: Section 3.2 of Szeliski's text.
Optional Reading: Sections 3.4-5 of Szeliski's text.
Sept. 22
Tutorial Material
Intro to SVD with Applications in Vision.
Sept. 27-30
Lecture Notes
Image Features: Part I
Image Features: Part II
Required Reading: Sections 4.1 and 4.2 of Szeliski's text.
Sept. 29
Tutorial Material
HoG example code.
Sept. 30 - Oct. 4
Lecture Notes
Image Features: Part III
Normalized LoG of Sunflowers Image: nrmLoG_Sunflowers.avi (1.7Mb)
Required Reading: References Lowe (2004) and
Bay et al, (2008), as cited on last page of "Image Features: Part III" lecture
notes.
Oct. 7-14
Lecture Notes
Image Landmark Applications
Parameter Estimation
Required Reading: Sections 6.1 and 6.2 and Appendices B1 through B3
of Szeliski's text.
Oct. 13
Tutorial Notes
Derivations for Estimation Notes
statEfficiencyDemo.m
Oct. 14-18
Lecture Notes
Parameter Estimation with Data Outliers
Matlab Estimation Demos
Oct. 18
Lecture Notes
Edge Detection
Oct. 21- Nov. 1
Lecture Notes
Epipolar Geometry
Required Reading: Sections 7.1 and 7.2
of Szeliski's text.
Matlab Homography and F-matrix Estimation Demos
Nov. 3 - 10
Lecture Notes
Image Motion
Reading: Fleet and Weiss Chapter
Reading: Sections 8.1 and 8.2
of Szeliski's text.
Nov. 15 - 22
Lecture Notes
Multi-Frame Reconstruction
Reading: Section 7.3
of Szeliski's text.