TNM067 - Scientific Visualization - 2017

Teachers: 

Ingrid Hotz email

Lab Assistants: 

Rickard Englund email, Robin Skånberg email

Course abstract:

The purpose of visualization is to allow the user to gain insight into data by representing the data through images. As data can originate from various sources, e.g., medical CT scanners, weather simulation or stock trading logs, different visualization metaphors are needed to represent the data in a meaningful way. Traditionally, visualization is split into two subfields: information visualization and scientific visualization. While information visualization deals with the representation of abstract data often stored in spreadsheets, scientific visualization deals with data, which has an inherent spatial component. Within this course we will focus on scientific visualization and learn how to transform spatial data - which might also have a temporal component - into meaningful visual representations. We will learn how the image representations generated through this transformation process can be both, expressive and - in order to allow interactive visualization - also be generated rapidly.
The course starts with an introduction to visualization, before it focuses on the basics of visualization, such as the visualization pipeline, data representations and fundamental algorithms for scalar and vector visualization. Volume rendering, which exploits besides color also transparency, is covered in an extra block, as it is an essential part of scientific visualization. Finally, perceptual and cognitive aspects are reviewed as knowledge about the human visual system is essential in order to generate expressive visualizations.

News: 

 

2017-10-16

 

  • Added information abot question session under the Exam sections 

 

2017-10-09

  • Information about exam added. 
     

2017-08-05

  •  Lecture notes for Chapter 1 and 2 is uploaded, find them here

 

2017-08-04

  •  Lab 1 instructions updated

2017-08-01
  • Lab 1 files and instructions uploaded , find them here
  • Lecture notes from laste year is uploaded and can be viewed here

 

2017-07-28

  • First lecture: Thu, Aug 31th, Room: K25
  • First lab: Tue, Sept 5th, Room K4507

 

Exam

To pass the course each student have to pass an Oral exam (in addition to the labs) in which theoretical questions will be asked and your responses will be grades according to your answers. 

During week 43 there will be 25 slots available to take this oral Exam. Please sign up on this doodle, select one timeslot that fits you. Each slot is 30 min long and will be held in K2070 (Ingrids office in Kopparhammeren 2, second floor) 

 

To practice for the exam you study the slides and go through the exercises uploaded to the materials webpage

 

 

Question session

On Wednesday the 18th October at 16:00 there will be a question session in the conference room KO202 in Kopparhammaren 2 in which there will be opportunity to discuss questions related to the exam. 

Materials

Course material such as Slides, Excercices will be uploaded at here, username and password will be emailed out to all student registered for the course, if you haven't got an email, please send an email to Rickard Englund. 

Laborations

These labs will be using Inviwo, a framework for interactive visualization. More information about labs will be online within a few days.

Lab schedule

There are a total of 4 labs to be completed and 6 scheduled lab sessions, 4 hours each. They will all be in the Windows 3D lab (K4507).
Date/Time Lab
Tue Spet 5th 13:15-17:00 Lab 1
Tue Spet 12th 13:15-17:00 Lab 2
Tue Spet 19th 13:15-17:00 Lab 1 and 2 Deadline to present Lab 1 and 2
Tue Spet 26th 13:15-17:00 Lab 3
Tue Oct 3th 13:15-17:00 Lab 4
Tue Oct 10th 13:15-17:00 All labs Deadline to present Lab 3 and 4

Master Thesis in scientific Visualization:

We always have a lot of interesting visualization projects as master thesis to offer. The focus of projects ranges from rendering questions to data analysis, form more software development tasks to more theoretical questions. Applications can be found in many different areas including natural science, medicine and engineering.