Course analysis 2D1257 Visualisation, 4p Spring 2004

Course data

Staff

Course responsible
Kai-Mikael Jää-Aro
Other teachers:
Ulf Andersson
Sten-Olof Hellström

Extents

16 h lecture, 8 h supervised lab

A laboratory exercise worth 2 points, one written exam worth 2 points, four exercises giving bonus points on the exam.

30 students (2 D, 3 E, 4 F, 18 IM, 1 M,2 MD) according to res registrations.

Course literature

OpenDX - Paths to Visualization by David Thompson, Jeff Braun and Ray Ford.
"Visualization of Scattered Meteorological Data: Study of Severe Rainfall Events in Northwestern Peru", by Lloyd A Treinish, Proceedings of the 1996 IBM Visualization Data Explorer Symposium, 1996.
"Why Should Engineers and Scientists Be Worried About Color?", by Bernice E Rogowitz and Lloyd A Treinish, 2001.
"Perceptual Techniques for Scientific Visualization", by Christopher G Healey, SIGGRAPH '99 Course Notes #6, 1999.
"Imaging Vector Fields Using Line Integral Convolution", by Brian Cabral and Leith Leedom, Computer Graphics 27(4), 1993.
"Visualizing Multivalued Data from 2D Incompressible Flows Using Concepts from Painting", by R M Kirby, H Marmanis and D H Laidlaw, IEEE Visualization, 1999.
"Marching Cubes: A High Resolution 3D Surface Construction Algorithm", by William E Lorensen and Harvey E Cline, Computer Graphics 21(4), 1987.
"Conveying the 3D Shape of Smoothly Curving Transparent Surfaces via Texture", by Victoria Interrante, Henry Fuchs and Stephen M. Pizer, IEEE Transactions on Visualization and Computer Graphics, 3(2), 1997.
"Showing Shape with Texture—Two Directions are Better than One", by Sunghee Kim, Haleh Hagh-Shenas and Victoria Interrante, 2003.

Student performance

By the end of the semester, the results were as follows:
U
3
(G)
4
5
(VG)
D 0 1 0 0
E 0 1 1 1
F 0 2 1 1
IM 1 6 3 6
M 0 1 0 0
MD - - - -
Total 1 11 5 8
Thus 80% of the students have passed the exam.

The laboratory exercise results:
G
D 1
E 3
F 3
IM 15
M 1
MD 0
Total 25
83% of the students have passed the laboratory exercise.

23 students (77%) have passed the entire course. Total credit production: 98 p.

Teaching

We have tried to combine theoretical lectures with immediately following hands-on exercises on the just covered material. To encourage work on these exercises the students were given bonus points on the exam if the exercises were demonstrated before a given deadline.

Examination

The examination was both an ungraded laboratory exercise and a written exam.

The laboratory exercise was performed in groups of two students and then presented both as a written report and a demonstration of the developed visualisation (of airflow in two different rooms).

The written exam was based on a few questions on terminology and theory and the rest on practical application of visualisation methods on various example data.

Course evaluation

A course evaluation questionnaire was done in ace. Four students responded to this. Their comments can be summarised as follows:

They did not find the course very difficult and it didn't take up too much of their time. In fact the level may even have been seen as slightly too low. No particular article, nor lecture, seemed to stand out as particularly good or bad.

At the same time I personally got the impression that some students did have problems with assimilating the material. This would suggest that there was a wide range of background knowledge among the students. This is not inconsistent with the experience from earlier years.

There are plans under way to develop an entire Master's programme in visualisation. The current course in visualisation could then be used as an introduction to scientific visualisation, not having to cover quite as much ground but could go deeper into algorithms and methods.

I still have not been able to find a good recent text book in scientific visualisation. The hunt goes ever on and on.