Course Visualization

  • Instructor: Prof. Dr. Bernd Fröhlich and Dr. Patrick Riehmann
  • Teaching assistants
    • Dr. Patrick Riehmann
    • M.Sc. Carl-Feofan Matthes
  • Lecture schedule 
    • Thursday, 13:30-15:00
    • First lecture: April 4, 2019
    • Location: Room 015, Bauhausstr. 11
  • Lab class schedule
    • Tuesday, 17:00 - 18:30 (Master CS4DM + Master HCI)
                      18:30 - 20:00 (Bachelor Medieninformatik, Master Digital Engineering)
    • First lab class: April 16, 2019
    • All lab classes will take place in the LiNT-Pool, Bauhausstr. 11
  • Target audience
    • B.Sc. Medieninformatik
    • M.Sc. Computer Science and Media
    • M.Sc. Computer Science for Digital Media
    • M.Sc. Human-Computer Interaction
    • M.Sc. Digital Engineering
    • M.Sc. MediaArchitecture
  • ECTS Credits
    • 4.5 Credits (MI, CSM, CS4DM, HCI)
    • 6 Credits (DE, MA)
  • Office hours by appointment only

Course Description

The first part of this course presents fundamental and advanced information visualization techniques for multi-dimensional and hierarchical data, graphs, time-series data, cartographic and categorical data. During the second half, algorithms and models for the scientific visualization of volumetric and vector-based data as well as corresponding out-of-core and level-of-detail techniques for handling very large datasets are introduced.

Various approaches presented in lectures will be studied, in part practically through labs and assignments, and with case studies. Lab classes focus on implementing, testing and evaluating the visualization approaches presented during the lectures. This course will be taught in English.

News

  • Lectures moved to Bauhausstr. 11, Room 015
  • Please have a look at the videos of the lectures which will come online every week
  • Exam preparation session 1: at beginning of project presentations on Sept 4, 10am, DBL top floor
  • Extended exam preparation and Q&A session: Sept 17, Bauhausstr. 11, R015, 10am

Lecture Notes

The documents from last year serve as a basis and will be further developed. The video material and the lecture pdfs (Adobe reader works best) are only available for your personal use! By downloading the material you agree that you do not further distribute it. The pdf files are only available from within the university network or through vpn.

Lab class material

Information Visualisation (Contact: patrick.riehmann(at)uni-weimar.de)

Scientific Visualization (Contact: carl-feofan.matthes(at)uni-weimar.de)

Final Project

In the final student project, students develop and implement a small visualization system, building on the foundations taught in the course. The individual topics of the student projects should be coordinated with the lab class instructors. Student projects are graded based on a public presentation to the instructors and the other students at the end of the term. Each group has to present their running system along with a few overview slides detailing their idea and approach to the topic.

  • Deadline for submission of student projects: September 2, 2019
  • Date of the student project presentation: September 4, 2019, 10 am, DBL Top Floor

     

Written Exams

  • Exam preparation session 1: at beginning of project presentations on Sept 4, 10am, DBL top floor
  • Extended exam preparation and Q&A session: Sept 17, 10am, Bauhausstr. 11, R015
  • Regular exam: September 23th, 10 am, Audimax
    • Use BISON for registration
  • Alternative oral exam in exceptional cases
    • For registration contact Prof. Fröhlich by email, explain why you cannot take your exam during the regular exam week and suggest a date for an oral exam.

Grading

  • Grading Information
    • 20 points can be achieved in the lab classes
    • 30 points can be achieved in the final student project
    • The following scheme lists the grades depending on the percentage of the achieved points:
      • 1.0   >=95.0
      • 1.1   [93.5-95.0)
      • 1.2   [92.0-93.5)
      • 1.3   [90.5-92.0)
      • 1.4   [89.0-90.5)
      • 1.5   [87.5-89.0)
      • 1.6   [86.0-87.5)
      • 1.7   [84.5-86.0)
      • 1.8   [83.0-84.5)
      • 1.9   [81.5-83.0)
      • 2.0   [80.0-81.5)
      • 2.1   [78.5-80.0)
      • 2.2   [77.0-78.5)
      • 2.3   [75.5-77.0)
      • 2.4   [74.0-75.5)
      • 2.5   [72.5-74.0)
      • ...
      • 3.0   [65.0-66.5)
      • ...
      • 4.0   [50.0-51.5)
      • Less than 50% is insufficient for an admission to the exam.
  • Contributions to the final grade
    • assignments:  20%
    • final project:   30%
    • final exam:     50%