Module 19339 (2005)

Syllabus page 2005/2006

06-19339
Computational Vision

Level 2/I

Jeremy Wyatt
10 credits in Semester 1

Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus


The Module Description is a strict subset of this Syllabus Page. (The University module description has not yet been checked against the School's.)

Changes and updates

New module for 2005/06.


Relevant Links


Outline

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.


Aims

The aims of this module are to:

  • 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

Learning Outcomes

On successful completion of this module, the student should be able to: Assessed by:
1make informed choices about which sort of algorithms to apply to solve specific problemsExamination
2use standard vision libraries or software to construct working vision systemsPractical work, Examination
3apply algorithms to simplified problems by handExamination
4discuss the advantages and drawbacks of different methods, explaining their workingPractical work, Examination

Restrictions, Prerequisites and Corequisites

Restrictions:

None

Prerequisites:

None

Co-requisites:

None


Teaching

Teaching Methods:

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

Contact Hours:

Approx. 35


Assessment

  • Supplementary (where allowed): As the sessional assessment
  • The continuous assessment consists of a team project.

Recommended Books

TitleAuthor(s)Publisher, Date
Computer VisionDana Ballard & Chris BrownPrentice Hall, 1982
Computer Vision: A Modern ApproachDavid Forsyth & Jean PoncePrentice Hall, 2003
Algorithms for Image Processing and Computer VisionJ R ParkerWiley, 1996

Detailed Syllabus

Not applicable

Last updated: 13 May 2005

Source file: /internal/modules/COMSCI/2005/xml/19339.xml

Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus