Computer Vision - MSc seminars

This page contains information specifically related to the Computer Vision seminars for MSc students. For general course material, and information for BA/BSc students, please return to the main course page.

First assignment

For the first assignment, choose one essay from the following list, or do the first programming exercise (details to follow on main course web page).

The deadline is Thursday 8 February. The essay should be 2000 - 3000 words. Please see the bibliography for reading.

  1. Techniques for edge detection.
  2. Shape recognition by template matching.
  3. Can J.J. Gibson's work contribute to the design of computer vision systems?
  4. Discuss critically Marr's theory of early vision.

The assignment does not contribute to your formal assessment for the degree.

Talk topics

You are asked to present one 20-minute talk during the term. We will have one or two talks each week, starting in week 3.

Please email David Young with your preferred date and topic. Suggestions for topics are below but you can propose your own. Booked topics have a name beside them below.

You should discuss your talk with David Young a week or so before you are due to give it; he will suggest specific reading.

Topic Week Name
Human stereo vision 6 Sveinn
Vision for autonomous guided vehicles 6 David
Stereo vision and epipolar geometry 7 Ropertos
Segmentation by simulated annealing 7 Aya
Satellite and aerial image interpretation 8 Jon
Character/handwriting recognition 8 Kuntal
Medical applications of computer vision 9 Mounir
Face recognition 9 Oliver
Edge and ridge detection  
Colour vision  
Vision for industrial robotics  
Visual control of flight  
Neural networks for object recognition  
Recognition of biological motion  
Neural networks in low-level vision  
Affordances and enactive perception  
Eye tracking  
Active Vision  
J.J. Gibson and computer vision  
Level set methods  
Wisard  
Line drawing analysis  
Concepts of dynamic vision  
General applications of computer vision  

Additional material

Log-polar line detection

Competitive learning Matlab demo

Radial basis function Matlab demo

Fourier transform Matlab demo

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