This module is inactive in the selected year. The information shown below is for the academic year that the module was last running in, prior to the year selected.

2014/15 Taught Postgraduate Module Catalogue

COMP5880M Scientific Visualization

15 creditsClass Size: 30

Module manager: Dr David Duke
Email: d.j.duke@leeds.ac.uk

Taught: Semester 2 (Jan to Jun) View Timetable

Year running 2014/15

Pre-requisites

COMP5930M

Scientific Computation

This module is not approved as an Elective

Objectives

On completion of this module, students should be able to:
- Understand the use of visualization in interpreting data
- Understand different kinds of data and how these fundamentally determine visualization methods;
- Understand core technical concepts, including data representation and processing models;
- Understand major algorithms for classes of data, including how and when they are used;
- Use a visualization toolkit API to construct visualizations of a new dataset;
- Articulate the relationship between visualization and fundamental computational methods;
- Identify performance characteristics and bottlenecks in a visualization algorithm;
- Implement and critique a new visualization technique.

Syllabus

I: Foundational material

- origins, rationale and development of scientific visualization;

- continuous fields versus discretely sampled data;

- types of data: scalar, vector, and tensor, and how they arise;

- the visualization pipeline model;

- representing data - exploiting geometric and topological regularity;

- visualization using VTK

- scalar algorithms, including isosurfacing and volume rendering;

- vector algorithms, including hedgehogs and streamtubes;

- rendering and interaction;

- further tools: probing, cutting, glyphing, resampling;

- introduction to image-based algorithms;

- "under the bonnet" - efficient data structures for meshes and volumes;

II: One or more of the following advanced topics:

- computational geometry: Voronoi diagrams, Delaunay triangulations, convex hulls;

- computational topology: Reeb graphs and Morse-Smale complex;

- Parallel visualization using ParaView;

- illustrative visualization;

- linking scientific and information visualization;

Teaching methods

Delivery type	Number	Length hours	Student hours
Laboratory	11	1.00	11.00
Lecture	22	1.00	22.00
Private study hours			117.00
Total Contact hours			33.00
Total hours (100hr per 10 credits)			150.00

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Assignment	Coursework	20.00
Assignment	Coursework	10.00
Assignment	Coursework	10.00
Total percentage (Assessment Coursework)		40.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Exams

Exam type	Exam duration	% of formal assessment
Standard exam (closed essays, MCQs etc)	2 hr	60.00
Total percentage (Assessment Exams)		60.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

There is no reading list for this module

Last updated: 06/08/2014

Disclaimer

Browse Other Catalogues

• Undergraduate module catalogue
• Taught Postgraduate module catalogue
• Undergraduate programme catalogue
• Taught Postgraduate programme catalogue

Errors, omissions, failed links etc should be notified to the Catalogue Team.PROD