Lecture: Scientific Visualization (Modul ISV)

[LSF] [MÜSLI] [Moodle]

Important

2017-07-25:We provide an additional slot for oral exams: August 17, 2017.
2017-07-24:Oral exams take place August 8, August 9, September 21, and September 22, 2017. Please register for one of these dates in MÜSLI. The location of the exams will be announced in MÜSLI.
2017-04-25:Exercises take place Tuesdays 09:15–10:45 in room SR 9.
2017-04-18:Please register both in MÜSLI and Moodle for the exercises. The password for Moodle access is provided in the lecture. The exercises have to be handed in via Moodle.

Lecturer

Prof. Dr. Filip Sadlo

Assistants

Naghmeh Fazelin.fazeli@stud.uni-heidelberg.de

Contact

sadlo@uni-heidelberg.de

Description

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.

Content

  • 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

Schedule

Lecture

Tuesday   11:15–12:45   INF 205, SR C   
Wednesday   09:15–10:45   INF 205, SR C   

Exercises

Tuesday   09:15–10:45   INF 205, SR 9   [MÜSLI]

Suggested Prerequisites

  • Einführung in die Praktische Informatik
  • Programmierkurs
  • Algorithmen und Datenstrukturen
  • Computergraphik (1 & 2) / Computer Graphics
  • Geometric Modeling and Animation

Literature

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