Hamid Dehghani

University of Birmingham
School of Computer Science

Computational Vision



The course notes that I use for Lectures, plus Lab handouts can be found here.
Note, that not all the material I deliver in lectures will have an associated handout, so you need to make sure that your in-class note taking is up to date. This does mean that you NEED to attend all the lectures.
Also, be sure to look for regular updates, and Announcement.

Lecture Notes

Lecture 1: Lecture 1: Introduction to Computational and Human Vision.
Lecture 2.1 Lecture 2.1: Human Vision.
Lecture 2.2 Lecture 2.2: Edge Detection.
Lecture 3.1 Lecture 3.1: Human Vision: Colour.
Lecture 3.2 Lecture 3.2: Noise Filtering.
Lecture 4.1 Lecture 4.1: Hough Transform.
Lecture 5.1 Lecture 5.1: Group Activity.
Lecture 5.2 Lecture 5.2: Reciever Operator Analysis.
Lecture 5.3 Lecture 5.3: Face Recognition.
Lecture 6.1 Lecture 6.1: Motion.
Lecture 7: History and Application of Computational Vision: Guest Lecture by Prof Ales Leonardis
Lecture 8.1 Lecture 8.1: Object Recognition.
Lecture 8.2 Lecture 8.2: Model Based Object Recognition.

Lecture Videos

These are recordings of the lectures associated with each handout:
Lecture 1.1 Introduction to Computational Vision
Lecture 1.2 Introduction to Human Vision
Lecture 2.1 Human Vision
Lecture 2.2 Edge Detection and Filtering
Lecture 3.1 Human Vision: Colour
Lecture 3.2 Noise Filtering
Lecture 4.1 Hough Transform
Video from Lectures 5.1 and 5.2 did not record!
Lecture 6.1 Part a Motion Detection
Lecture 6.1 Part b Moravec operator

Labs

All labs are on Fridays.
Students with surname initials A-J at 11.00 - 12.00 in LG04, School of Computer Science
Students with surname initials K-Z at 12.00 - 13.00 in LG04, School of Computer Science
Attendance WILL BE monitored.
Lab 1: Matlab Tutorial The goal of the tutorials here is to provide a simple overview and introduction to matlab. The tutorials are broken up into some of the basic topics. The first includes a few examples of how Matlab makes it easy to create and manipulate vectors. The tutorials move from the simple examples and lead to more complicated examples.
Lab 2: Edge Detectors. You will also need to download these files. Click here. Note that short write-up is due on Friday 25th January 2013, 12.00 noon, to be submitted into the box outside CS Reception.
Lab 3: Noise Removal. You will also need to download these files. Click here. Note that short write-up is due on Friday 1st Feb 2013, 12.00 noon, to be submitted into the box outside CS Reception.
Lab 4: Hough Transform. You will also need to download these files. Click here. Note that short write-up is due on Friday 8th Feb 2013, 12.00 noon, to be submitted into the box outside CS Reception.
Lab 5: Eigenfaces You will also need to download these files. Click here. Note: No write up needed for this lab


Assessed Assignment


The guidelines for your assessed assignments are now available.
Note: You are to work in pairs or thress for this assessment, and produce one report.
The report should be handed in via School Reception by 12 noon on the 22nd March 2013.
Assessing the relative contribution of each partner
You will need to submit one completed form per project write-up (i.e. one per group). Download form here.
The purpose of this marking scheme is to take account of the relative contribution of partners in the project. This is a scheme based on consensus, in which you must try to agree the rating for each team member after discussion.

Announcements

13th Feb 2013
Details of your Assessed work are now available.
9th Jan 2013
First Lecture: Friday 11th Jan at 9 am in LT3 Sport and Excercise Science.
9th Jan 2012
We have over 70 students on this module and are unfortunately limited by the number of MATLAB licenses we have.
To overcome this, I have arranged the following:
We will have TWO lab sessions on Fridays:
11.00 am for all students with surname initials A-J
12.00 am for all students with surname initials K-Z