Subject description - BE4M39VIZ
Summary of Study |
Summary of Branches |
All Subject Groups |
All Subjects |
List of Roles |
Explanatory Notes
Instructions
| BE4M39VIZ | Visualization | ||
|---|---|---|---|
| Roles: | PO | Extent of teaching: | 2P+2C |
| Department: | 13139 | Language of teaching: | EN |
| Guarantors: | Čmolík L. | Completion: | Z,ZK |
| Lecturers: | Čmolík L., Slavík P. | Credits: | 6 |
| Tutors: | Čmolík L. | Semester: | L |
Anotation:
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.Course outlines:
| 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 |
Exercises outline:
| 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 |
Literature:
| 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 |
Requirements:
Webpage:
https://moodle.fel.cvut.cz/course/B4M39VIZ Subject is included into these academic programs:| Program | Branch | Role | Recommended semester |
| MEOI9_2016 | Data Science | PO | 2 |
| MEOI1_2018 | Human-Computer Interaction | PO | 2 |
| MEOI3_2018 | Computer Graphics | PO | 2 |
| MEOI3_2016 | Computer Graphics | PO | 2 |
| MEOI1_2016 | Human-Computer Interaction | PO | 2 |
| MEOI9_2018 | Data Science | PO | 2 |
| Page updated 26.2.2021 17:52:17, semester: Z/2020-1, L/2021-2, L/2020-1, Z/2021-2, Send comments about the content to the Administrators of the Academic Programs | Proposal and Realization: I. Halaška (K336), J. Novák (K336) |