Number of hours
- Lectures 18.0
- Projects -
- Tutorials -
- Internship -
- Laboratory works 12.0
- Written tests -
ECTS
ECTS 3.0
Goal(s)
Supercomputer simulations, imaging devices and sensors produce massive datasets. In order to gain understanding of the physical, chemical, medical or environmental phenomena hidden in the data, one of the premium means is to show a visual representation of the dataset. This is the goal of Scientific Visualization. In this lecture we will first give an overview of Visualization. Then we will present in detail some of the main techniques used to extract meaningfull part of the data and to visualize them in a efficient and illustrative manner. Furthermore, a visualization project will be developed. The project will be based on publicly available air quality and weather observation datasets. On a reduced scale, all steps of a real-world visualization system, e.g. reading the data, interpolating it properly, extracting part of it and finally produce different visualizations of it will be developed.
Responsible(s)
-
Content(s)
Introduction to visualization
Classification and representation of data
Multiresolution modeling
Isosurface techniques
Direct volume rendering
Scattered data visualization
Vector field visualization
Visualization project for environmental datadescription soon…
MATLAB, C/C++, Unix
Test
personal work on computer, short presentation and report
The exam is given in english only 
Calendar
The course exists in the following branches:
- Curriculum - Master 2 in Applied Mathematics - Semester 9 (this course is given in english only
)
Additional Information
Course ID : WMM9AM08
Course language(s):
You can find this course among all other courses.
Bibliography
A. Watt, M. Watt: Advanced animation and rendering techniques, Addison Wesley
Nielson G, Hagen H, Mueller H: Scientific Visualization, Overviews, Methodologies, and Techniques,
IEEE Computer Society Press, 1997.
Bajaj C: Scientific Visualization Techniques, John Wiley and Sons, 1997.