Data Analysis and Visualization

The goals of this lecture are to understand the basic computer graphics, visualization, and Virtual Reality techniques and methods. Furthermore, it is the goal to present the entire computer graphics and visualization pipeline from raw data emerging from simulation to meaningful images, animations, and interactive visualizations in 2D and 3D space.
The content of the lecture reads as follows:

• Introduction to the rendering pipeline: data structures, transformations, homogeneous coordinates, culling, projection, clipping, hidden surface removal, Phong reflection model, shading, anti-aliasing, computer graphics hardware
• Introduction to visualization, the visualization pipeline, classification of data types (scalars, vectors, graphs, ...)
• Introduction to human perception, with a focus on visual perception, Gestalt laws, node link diagrams
• Scalar field visualization: transfer function design, iso-contouring, volume rendering
• Vector field visualization: glyphs, flow lines, streak lines, iso-lines, vector field integration schemes, line integral convolution
• Introduction to data analysis, dimension reduction, principal component analysis, manifold detection & reconstruction
• Explorative analysis of simulation datasets in Virtual Reality: stereoscopic projections, Virtual Reality hardware, parallel software architectures for virtual environments, 3D interaction methodology, navigation in space and time
• Advanced realtime rendering
• Visualization of (abstract) multi-dimensional data, Information Visualization
• Graph visualization: data structure for graphs, layout algorithms, edge bundling, graph theory and algorithms