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CEG4520/CEG4520 - Scientific Visualization and Virtual Environments



Scientific visualization as a research area has impacted an enormous number of engineering disciplines. In particular, it helps users get better insight into their data. In many areas, it is almost impossible to reasonably analyze data without an appropriate visualization due to the overwhelming amount of information present in the data. Data sets resulting from simulations or experiments in various application fields, for example computational fluid dynamics (CFD) or medical imaging, have to be analyzed and represented in a way that the user is enabled to easily investigate and explore the data. Generally, the software environment becomes more and more illustrative. For example, the emerging of Google maps and Google Earth underlines this. This course will provide you with techniques for generating visualizations of various different data types, including scalar, vector, and tensor data. Geometric as well as volumetric methodologies will be introduced. Advantages and disadvantages of the visualization methods are discussed to enable students to pick the optimal technique for a given type of data set. Different visualization environments are illustrated from common desktop environments to high-end virtual environments. Programming techniques for these environments are explained, including rendering techniques and different input paradigms. Programming examples are provided to enable students to immediately experience their own visualization application. Materials in this course are complementary to those in Computer Graphics I.

Course syllabus


The slides used during the lecture can be downloaded here:

Introductary slides

Chapter 1

Chapter 2

Chapter 3

Chapter 4

Chapter 5

Chapter 6

Chapter 7

Chapter 8

Chapter 9

Chapter 10

Chapter 11

Chapter 12

Chapter 13 (optional)

Proofs for different types of vector fields

OpenGL example for using Microsoft's Kinect with the Kinect SDK.

Example for getting positional data from a VRPN server

Midterm review sample questions

Last modified Friday December 06, 2019