Scientific Visualization and Virtual Reality

6 EC

Semester 1, period 2

5284SVVR6Y

Owner Master Computational Science (joint degree)
Coordinator dr. Rob Belleman
Part of Master Computational Science (Joint Degree),

Course manual 2022/2023

Course content

Within this course, concepts, algorithms and techniques of scientific visualization and virtual reality will be studied and a number of selected examples from computational science applications will be discussed and demonstrated. The course will cover the following subjects: the purpose of visualization, taxonomy of visualization, applications of scientific visualization, the computational science cycle, the visualization pipeline, glyph visualization, vector field visualization, surface visualization, volume visualization, interaction, virtual reality, augmented reality, interactive exploration environments, applications.

Study materials

Software

  • Paraview, VTK

Other

  • Papers and chapters on scientific visualization and virtual reality.

Objectives

  • The student can explain the working of the most important scientific visualisation algorithms
  • The student understands when and how Virtual Reality can be applied to scientific visualization
  • The student can construct a visualization of a scientific data set
  • The student can analyse the performance of a scientific visualization application
  • The student can reflect on the effectiveness of a scientific visualization

Teaching methods

  • Lecture
  • Computer lab session/practical training
  • Self-study
  • Working independently on e.g. a project or thesis

Lectures, demonstrations, assignments, visualisation project.

Learning activities

Activity

Number of hours

Lectures

14

Laptop session

14

Assignments

50

Visualisation project

70

Zelfstudie

20

Attendance

This programme does not have requirements concerning attendance (Ter part B).

Assessment

Item and weight Details

Final grade

0.15 (15%)

Exercise 1: Cars dataset

0.15 (15%)

Exercise 2: Simulating and visualising temperature distribution in a material

0.4 (40%)

Visualization project

Must be ≥ 5

0.3 (30%)

Exam

Must be ≥ 5

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Week Lecture topic Laptop session topics Assignment
1 Introduction to SVVR Visualisation Lab visit Cars
2 The Visualisation Pipeline Visualisation with Paraview Heat transfer
3 Visualisation in Computational Science Visualisation with VTK Project
4 Scientific Visualisation II Isocontours Project
5 Scientific Visualisation III Volume rendering Project
6 Scientific Visualisation IV Vector field rendering, AR Project
7 Biomedical visualisation and Virtual Reality (help with project) Project
8 (exam week)   Project

Timetable

The schedule for this course is published on DataNose.

Additional information

Recommended prior skills: computer graphics, programming in C, C++ or Python.

Contact information

Coordinator

  • dr. Rob Belleman