Lecture: Scientific Visualization

Course
- Lecturer(s):
- Start: April 8, 2015
- Dates: Mon. 16:30-18:00, Wed. 10:00-11:30, B-IT Main Lecture Hall
- Curriculum: B-IT Master Media Informatics , Bachelor
- Exams: Jul 15, 10-12; Sep 2, 10-12
Exercises
- Tutor(s):
- Start: April 15, 2015
- Dates: Wed. 11:45-13:15
Description
In today's world, ever-increasing amounts of measured, simulated, collected and stored data have turned the ability to make sense of large and complex data into a key qualification. The goal of visualization is to produce visual representations of data. It provides an intuitive, effective, and thus very popular means of quite literally gaining insight into complex phenomena. This lecture introduces the main concepts and techniques of data visualization. It focuses on visualizing volumetric data from science and medicine, but also covers more abstract data such as networks or graphs, and conveys fundamental knowledge about color, human perception, and graphics programming. Its mixture of theoretical and practical programming exercises will train the ability to find effective solutions for real-world problems based on a clear theoretical foundation. The topics of this lecture include: Color and perception, rendering 3D volume data (such as medical CT or MRI data), extracting surfaces from volumetric data, visualizing and identifying meaningful structures in vector fields (such as flow fields from computational fluid dynamics) and tensor fields (as they arise in engineering and modern neuroimaging), visualizing high-dimensional data, dimensionality reduction, clustering, and uses of machine learning in visualization. The course takes place in the main lecture hall of the B-IT building, Dahlmannstr. 2 (How to get there).
Slides
- Introduction (PDF document, 2.5 MB)
- Data (PDF document, 2.3 MB)
- Sampling-Interpolation (PDF document, 1.9 MB)
- Spaces-Transformations (PDF document, 1.1 MB)
- Color-Perception (PDF document, 3.8 MB)
- Indirect-Volume-Visualization (PDF document, 2.8 MB)
- Direct-Volume-Rendering (PDF document, 3.6 MB)
- Geometry-Based-Flow-Vis (PDF document, 3.9 MB)
- Image-Based-Flow-Vis (PDF document, 3.0 MB)
- Feature-Based-Flow-Vis (PDF document, 3.2 MB)
- Tensor-Vis (PDF document, 3.7 MB)
- Ridges-and-Valleys (PDF document, 1.6 MB)
- Multi-Dimensional-Data (PDF document, 2.9 MB)
Assignment Sheets
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Exercise 1: Installation Assignment sheet (PDF document, 629 KB)
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Exercise 2: IntroVtkVisTrails Assignment sheet (PDF document, 568 KB)
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Exercise 3: Sampling-Interpolation Assignment sheet (PDF document, 317 KB)
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Exercise 4: Spaces-and-Colors Assignment sheet (PDF document, 759 KB)
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Exercise 5: Colors-and-Isocurves Assignment sheet (PDF document, 2.3 MB)
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Exercise 6: Isosurfaces Assignment sheet (PDF document, 244 KB)
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Exercise 7: Direct-Volume-Rendering Assignment sheet (PDF document, 223 KB)
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Exercise 8: Geometry-Based-Flow-Vis Assignment sheet (PDF document, 1.2 MB)
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Exercise 9: LIC Assignment sheet (PDF document, 356 KB)
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Exercise 10: Feature-Based-Flow-Vis Assignment sheet (PDF document, 1.0 MB)
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Exercise 11: Tensor-Vis Assignment sheet (PDF document, 647 KB)
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Exercise 12: Trial-Exam Assignment sheet (PDF document, 324 KB) |
Additional Documents
- results-final-exam (PDF document, 34 KB)
Literature
- Alexandru C. Telea: Data Visualization - Principles and Practice, CRC Press, Second Edition, 2015
- C.D. Hansen, C. Johnson: Visualization Handbook, Academic Press, 2004
- B. Preim, C. Botha: Visual Computing for Medicine: Theory, Algorithms, and Applications, Morgan Kaufmann, 2014 (
officially available online within University of Bonn)
- K. Engel et al.: Real-Time Volume Graphics, A K Peters, 2006
- C. Ware: Information Visualization. Perception for Design, Morgan Kaufmann, 3rd edition, 2013
- M. Ward et al.: Interactive Data Visualization:Foundations, Techniques,and Applications. CRC Press, 2010