COMPUTER VISION (CITS4240)
The aim of this course is to provide an overview of digital image processing and computer vision analysis. Both areas are large enough to justify a course on their own; this 1-semester course covers the fundamentals of image formation, low-level image processing and enhancement in both the spatial and Fourier domains, and gives a flavour of higher level vision tasks by studying some of the Structure-from-X algorithms, such as Structure from Stereo, and Structure from Motion. Finally, we briefy cover some aspects of Shape from Shading and Photometric Stereo.
The course consists of 13 two-hour lectures and a weekly 2 hour laboratory session. The assessment for this course is via a 2 hour written examination at the end of the semester (for 70%) and a portfolio of practical laboratory exercises done throughout the semester (for 30%). Almost all the laboratory work is done using MATLAB.
Unit Coordinator, Lecturer, and Lab DemonstratorAssociate Professor. Du Huynh (Coordinator, Lecturer, Lab Demonstrator)
Room 1.22, CSSE Building
Consultation hours: Tuesdays 11:00am - 12:00pm
Additional casual Lab Demonstrator: TBA
With the absence of a suitable text a considerable amount of supplementary material has been prepared for the course over the years by Associate Professor Peter Kovesi and Winthrop Professor Robyn Owens. This material is not intended to replace the notes presented in lectures. Material presented in lectures may include areas not covered by these supplementary notes.
Note: Not all of the links below under Lectures and Laboratories are currently pointing to files that exist. As we progress through the semester, these links will start to point to the right place. It is your responsibility to constantly check this website to download the supplementary notes yourself.
Note: Lecture notes can be purchased from the University Bookshop in week 1 or 2 of the semester.
Lecture note coverpage ( pdf file )
The lecture slides for each of the above topics can be found in the /cslinux/examples/CITS4240/LectureSlides2012 directory. The easiest way to access them is via a Linux machine in a CSSE Laboratory.
Laboratories and PortfolioLaboratory exercises will be posted progressively over the semester. Do a 'reload' to ensure you have the most up to date links. The work done in these lab exercises (from Lab sheet 2 to Lab sheet 8) will form your portfolio of practical assessment. Note: The portfolio should be submitted to cssubmit by Thursday 31st of May 2012 (week 13) at 5pm. Your portfolio should be written in html. You should organize your portfolio so that related files (e.g. Matlab .m files, image files, html files) for each lab sheet are put together into subdirectories. Ensure that you submit all the required .m files so that your Matlab code can be tested. Provide description about any parameters for your code as well as the input and output images on the html pages. Ensure that there are no missing links on your web pages.
You should compress the entire portfolio into a zip or tgz file and submit that single file to cssubmit. You need to ensure that, when your file is uncompressed, the directory structure is retained.
More instructions (if needed) will be announced later in the semester.
Lab classes will start in week 2 of the semester.
How to construct your portfolio.
This document provides an introduction to HTML and also explains how
to save and resize images and plots from MATLAB for incorporation in
Some useful MATLAB references
TextsThere is no specific text book specified for the course. The recommended reading for this course includes:
Some useful links
Links marked with a * are outside PARNET. You will need to use the proxy server to access these sites.
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