Scientific Visualization

Lecturer: Dr. Filip Sadlo

Semester: WS 2014/15

Lecture: 4 SWS

Exercise: 2 SWS

Audience: Bachelor and Master

Credits: 8 ECTS


  • 2015-01-30: Monday lecture is rescheduled to Tuesday 3 February 16:15-17:45 *****
  • 2015-01-26: Doodle for oral exams is ready (see Moodle), please fill in
  • 2015-01-26: Doodle for lecture reschedule (from 2 February) is ready (see Moodle), please fill in until 29 January
  • 2015-01-09: Friday lecture (23 January) will take place in OMZ U014
  • 2014-12-19: No exercise assignment over Christmas
  • 2014-11-13: Monday lecture (17 November) takes place in OMZ U014
  • 2014-11-08: No lecture and no exercise next week, i.e., no lecture/exercise lesson from 10 to 16 November
  • 2014-11-03: Please register for the exercise in Müsli
  • 2014-11-02: Assignments can be submitted in groups of two, please simply supply both names on your submission
  • 2014-11-02: Due date of Assignment 1 postponed to 2014-11-04, 11 am, due to possible difficulties with Moodle
  • 2014-10-31: Exercises will take place Friday 9-11 am, INF 350 (OMZ), room U012 
  • 2014-10-28: You can start submitting solutions of Assignment 1
  • 2014-10-28, 13:40: Assignment 1 updated (added information for PDF generation)
  • 2014-10-28: Assignment 1 is online (in Moodle)
  • 2014-10-26: First exercise will take place 28 October, 11:15-12:45, at INF 350 (OMZ), room U012
  • 2014-10-26: Doodle for exercise slots is ready (see Moodle), please fill in until 31 October
  • 2014-10-22: Moodle access is ready
  • Lecture starts Friday 17 October


Visualization deals with all aspects that are connected with the visual representation of data sets from scientific experiments, simulations, medical scanners, databases and the like in order to achieve a deeper understanding or a simpler representation of complex phenomena. To obtain this goal, both well‐known techniques from the field of interactive computer graphics and completely new methods are applied. The objective of the course is to provide advanced knowledge about visualization algorithms and data structures as well as acquaintance with practical applications of visualization. Based on the visualization pipeline and the classification of mapping methods, this course will present advanced visualization algorithms and data structures for various kinds of applications and scenarios.


  • Introduction
  • Visualization Process
  • Data Sources and Representation
  • Interpolation and Filtering
  • Approaches for Visual Mapping
  • Scalar Field Visualization: Advanced Techniques for Contour Extraction, Classification, Texture-Based Volume Rendering, Volumetric Illumination, Advanced Techniques for Volume Visualization, Pre-Integration, Cell Projection, Feature Extraction
  • Vector Field Visualization: Vector Calculus, Particle Tracing on Grids, Vector Field Topology, Vortex Visualization, Feature Extraction, Feature Tracking
  • Tensor Field Visualization: Glyphs, Hue-Balls and Lit-Tensors, Line-Based Visualization, Tensor Field Topology, Feature Extraction



Monday, 11 am - 1 pm, INF 368 (IWR), Room 532
Friday, 11 am - 1 pm, INF 368 (IWR), Room 532


Friday, 9 - 11 am, INF 350 (OMZ), Room U012

Suggested Prerequisites

  • Einführung in die Praktische Informatik
  • Programmierkurs
  • Algorithmen und Datenstrukturen
  • Grundlagen der wiss. Visualisierung


  • C.D. Hansen, C.R. Johnson, The Visualization Handbook, 2005.


  E-learning course