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Visualization

Course in German and/or English (inquiry recommended)

Hours per Week:

4

Credit Points:

5

Prerequisites:

Foundations of computer science, algorithms and data structures, computer graphics, programming experience (C++, Python), mathematics (esp. linear algebra, differential and integral calculus)

Type of Course:

Lecture and seminar

Frequency (WS/SS):

Sommersemester

Work Load:

150 hours, thereof
  60 contact time
  90 hours lecture preparation, postprocessing and exercises 

Study Programme Goals:

Visualization of data from simulations or experiments is a fundamental application area of computer science for gaining insight into the meaning of the data. Methods and algorithms used for visualization applications can be applied to a wide range of practical problems. 

Course Goals:

Analysis and comparison of fundamental algorithms for the visualization of technical and scientific data. Dermination of the applicability of different methods for specific application areas. Development of strategies for solving new problem areas. 

Key Qualifications:

Analysis and classification of problems, problem solving with creativity, bbility to understand big, complex systems, learning from examples, ability to transfer knowledge and methods

Course Contents:

Visualization includes all aspects related to the visual preparation of usually large data sets from technical or scientific experiments and simulation. For a better understanding and a meaningful representation of complex phenomena, methods from interactive computer graphics are applied. This lecture introduces basic algorithms and data structures and gives an overview of available software tools and common data formats.

The lecture covers the following topics:

  • Scenarios for visualization
  • Meshes and data representation
  • Methods for 2D scalar and vector fields
  • Methods for 3D scalar and vector fields
  • Methods for multivariate data
  • Volume rendering with iso-surfaces
  • Direct volume rendering


Literature:

  • W. Schroeder and K. Martin, "The Visualization Toolkit", Kitware Inc. 2004
  • M. Ward, G.G. Grinstein and D. Keim, "Interactive Data Visualization: Foundations, Techniques, and Applications", Taylor & Francis, 2010
  • C.D. Hansen and C.R. Johnson, "Visualization Handbook", Academic Press, 2004 

Comments:

 

Assessment/Examination:

Written Exam (90 Minutes, 100%)

Admission Requirement:

 

Auxiliary Means:

 5(5), 7

Lecturer(s):

Prof. Dr. Teßmann





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