13 May 2005 provide a general introduction to computer vision give an overview of computational models of visual processing in animals introduce a number of different frameworks and representations for vision familiarise the student with a number of techniques and algorithms in computer vision provide a foundation for further study in the area of computer vision make informed choices about which sort of algorithms to apply to solve specific problemsExamination use standard vision libraries or software to construct working vision systemsPractical work, Examination apply algorithms to simplified problems by handExamination discuss the advantages and drawbacks of different methods, explaining their workingPractical work, Examination

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2 hrs lectures per week, 1 hr lab/exercise class

 Approx. 35

1.5 hr examination (70%), continuous assessment (30%). Resit by examination only.

The continuous assessment consists of a team project.

 The module provides an introduction to computer vision, intended for students with some prior background in AI. Appropriate computational models, techniques and algorithms will be introduced, so that students can both understand the relevant literature and construct simple sofware systems.

To be written.

 Computer Vision Dana Ballard & Chris Brown Prentice Hall 1982 Computer Vision: A Modern Approach David Forsyth & Jean Ponce Prentice Hall 2003 Algorithms for Image Processing and Computer Vision J R Parker Wiley 1996