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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2019/2020

Advanced Visualization Methods

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Code Completion Credits Range
XP39VIZ ZK 4 2P
Lecturer:
Ladislav Čmolík (guarantor), Pavel Slavík (guarantor)
Tutor:
Supervisor:
Department of Computer Graphics and Interaction
Synopsis:

Human factors in visualization (Perception and cognition, Visual saliency, Visual thinking)

Design of User Interfaces for Visualization applications (Evaluation of visualization techniques)

Advanced volume visualization (Illustrative volume rendering)

Big data visualization, Visual analytics, Animation for visualization, Data compression and reduction

Large scale data visualization

Visualization techniques in nonstandard environment

Requirements:

It may be beneficial for students to pass course Visualization in MSc. track

Syllabus of lectures:

1.-2. Human factors in visualization. Perception and cognition. Visual thinking.

3.-4. Design of user interfaces for visualization applications. Methods for evaluation of visualization techniques.

5.-6. Advanced methods for volume visualization. Illustrative volume rendering.

7.-8. Visualization of big data. Visual analytics. Visualization and animation. Data compression.

9.- 10. Visualization of data acquired from various sources (data in mu1timodal environment).

11.-12. Visualization in non-standard environments (mobile environment, virtual reality etc.]

13.- 14. New trends in data visualization

Syllabus of tutorials:

Acquaitance with the goal of seminars. Organization of excercises. Requirements for exam.

Semestral project.

Consultations to the project.

Study and presentation of particular topics in the field of visualization.

Final presentation of the project together with evaluation of results reached together with its contribution to dissertation to be.

Study Objective:

The goal ofthis course is to acquaint students with up to date methods of visualization where the attention is paid to

various fields where visualization may be used. Namely the wide coverage of the applications of visualization can be

considered innovative (in comparison with traditional approaches used worldwide up to now).

Study materials:

Tamara Munzer: Visualization Analysis and Design, AK Peters, 2014

Colin Ware: Visual Thinking for Design, Elsevier Inc., 2008

Nathan Yau, Data Points: Visualization that means something That Means Something, Wiley, 2013

Note:
Time-table for winter semester 2019/2020:
Time-table is not available yet
Time-table for summer semester 2019/2020:
Time-table is not available yet
The course is a part of the following study plans:
Data valid to 2020-05-30
For updated information see http://bilakniha.cvut.cz/en/predmet6040106.html