Popis předmětu - BE4M39VIZ
BE4M39VIZ | Visualization | ||
---|---|---|---|
Role: | PO | Rozsah výuky: | 2P+2C |
Katedra: | 13139 | Jazyk výuky: | EN |
Garanti: | Zakončení: | Z,ZK | |
Přednášející: | Kreditů: | 6 | |
Cvičící: | Semestr: | L |
Webová stránka:
https://moodle.fel.cvut.cz/course/B4M39VIZAnotace:
In this course, you will get the knowledge of theoretical background for visualization and the application of visualization in real-world examples. The visualization methods are aimed at exploiting both the full power of computer technologies and the characteristics (and limits) of human perception. Well-chosen visualization methods can help to reveal hidden dependencies in the data that are not evident at the first glance. This in turn enables a more precise analysis of the data, or provides a deeper insight into the core of the particular problem represented by the data.Osnovy přednášek:
1. | Motivation for data visualization, history, categories of visualization 9infovis, scivis, software visualization,..) | |
2. | Visualization of scalar data (visualization pipeline, data reduction) | |
3. | Visualization of vector data (problems of visualization in 2D, 3D,..) | |
4. | Visualization of volume data (marching cube, cuberille) | |
5. | Visualization of volume data (volume data rendering, topological problems of volume data rendering,..) | |
6. | Visualization of dynamic data (animation, time scale,..) | |
7. | Information visualization (HomeFinder, TreeMaps, hyperbolic geometry) | |
8. | Perception and interpretation of visualized data (context, human perception, psychology of perception) | |
9. | Simulation and visualization (e.g. simulation and visualization of technological processes) | |
10. | Visualization of medical data (tomography. Operation planning) | |
11. | Technical illustration, medical illustration | |
12. | Software visualization (visualization of software behavior, visualization of software maintenance ,..) | |
13. | Problems of visual data mining. Applications of visual data mining (relation to neural computing) | |
14. | Reserve |
Osnovy cvičení:
1. | Semestral project assignement | |
2. | Semestral project assignement | |
3. | Consultations to semestral project | |
4. | Consultations to semestral project | |
5. | Consultations to semestral project | |
6. | Consultations to semestral project | |
7. | Checkpoint of semestral project | |
8. | Consultations to semestral project | |
9. | Consultations to semestral project | |
10. | Consultations to semestral project | |
11. | Consultations to semestral project | |
12. | Semestral project presentation | |
13. | Semestral project presentation | |
14. | Semestral project assessment |
Literatura:
1. | Fayyad, U., Grinstein, G.G., Wierse, A.: Information Visualization in Data Mining and Knowledge Discovery, Morgan Kaufmann, 2002 | |
2. | Stasko,J., Domingue,J., Brown,M.H., Price, B.A.: Software Visualization, MIT Press, 1998 | |
3. | Chen, Ch.: Information Visualization and Virtual Environments,Springer, 1999 |
Požadavky:
Poznámka:
Rozsah výuky v kombinované formě studia: 14p+6c |
Předmět je zahrnut do těchto studijních plánů:
Plán | Obor | Role | Dop. semestr |
MEOI1_2018 | Human-Computer Interaction | PO | 2 |
MEOI3_2018 | Computer Graphics | PO | 2 |
MEOI9_2018 | Data Science | PO | 2 |
Stránka vytvořena 25.9.2023 17:49:53, semestry: Z/2024-5, Z/2023-4, připomínky k informační náplni zasílejte správci studijních plánů | Návrh a realizace: I. Halaška (K336), J. Novák (K336) |