Module 17421 (2003)

Syllabus page 2003/2004

06-17421
Imaging and Visualisation Systems

Level 3/H

Peter Tino:5
Bob Hendley:5
10 credits in Semester 2

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

Relevant Links

Peter TiƱo's Module Page


Outline

Through both lectures and practical work, the module introduces a range of state-of-the-art techniques in the fields of imaging and visualisation. The 'information revolution' has generated large amounts of data, but valuable information is often hidden and hence unusable. Visualisation techniques seek to provide graphical answers to questions such as "How does the data look?", "What structures are there?" or "What model should be used?". Imaging techniques include the generation of realistic models, such as fractal models of landscapes. The module includes some practical work.


Aims

The aims of this module are to:

  • introduce the fields of imaging and visualisation
  • investigate the purposes of visualisation and the constraints imposed on visualisation systems
  • explore significant techniques in imaging and visualisation
  • enable students to independently extend the range of techniques that they can use

Learning Outcomes

On successful completion of this module, the student should be able to: Assessed by:
1demonstrate an understanding of the range of imaging and visualisation techniques available Examination
2analyse the requirements of visualisation applications Examination and coursework
3identify and justify suitable techniques to solve imaging and visualisation problems Examination and coursework
4use appropriate tools and techniques to produce visualisation systems Coursework
5demonstrate an understanding of the constraints of the human perceptual system Examination and coursework

Restrictions, Prerequisites and Corequisites

Restrictions:

Registration is limited to 25 students.

Prerequisites:

06-02504 (Graphics 1)

Co-requisites:

None


Teaching

Teaching Methods:

2 hours/week lectures/exercise classes plus labs

Contact Hours:

24+


Assessment

  • Supplementary (where allowed): As the sessional assessment
  • 2 hr examination (80%), continuous assessment (20%). Resit (where allowed) by examination only.

Recommended Books

TitleAuthor(s)Publisher, Date
Introduction to Visualisation and Virtual EnvironmentsChaomei ChenSpringer, 2002
Data Visualization: The state of the artFrits H. Post, Gregory M. Nielson, Georges-Pierre Bonneau (eds)Kluwer Academic, 2002
Fractals EverywhereMichael F. BarnsleyMorgan Kaufmann, 2000

Detailed Syllabus

  1. Introduction (1)
    • Motivations for visualisation
    • Properties of human perception
    • Overview of the range of visualisation techniques and applications
  2. Visualisation of vector and structured data (6)
    • Principle Component analysis
    • Factor Analysis
    • Latent Trait models
    • Enhancing the information content of visualisation plots
    • Hierarchical visualisation
  3. Fractal Images (4)
    • Mandelbrot set
    • Julia sets
    • Recurrent iterated functions
    • Fractal modelling of real world objects
  4. Scientific visualisation (3)
    • Isosurfaces, glyphs and other representations
    • Languages and techniques
    • Examples
  5. Information visualisation (6)
    • Features and feature extraction
    • Network visualisation
    • Text visualisation
    • Virtual environments

Last updated: 17 Mar 2004

Source file: /internal/modules/COMSCI/2003/xml/17421.xml

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