2016 Fall Quarter
Lecture: 3 hours
Discussion: 1 hour
Discussion: 1 hour
Computer graphics techniques for generating images of various types of measured or computer-simulated data. Typical applications for these graphics techniques include study of air flows around car bodies, medical data, and molecular structures. GE Prior to Fall 2011: SciEng. GE: SE, VL.
Pass One open to Computer Science and Computer Science Engineering Majors only.
Summary of Course Content
- Grid Structures Scientific data sets can be given without any given connectivity among the data (scattered data) or on a so-called structured or unstructured grid. Typical grids (rectilinear, curvilinear, prismatic, tetrahedral, etc.) are discussed and appropriate data structures and interpolation methods are introduced.
- Basic Scalar Field Visualization A variety of techniques for the visualization of scalar fields, i.e. functions of the form f(x,y) and f(x,y,z), are discussed. Algorithms that use color and/or opacity to represent the scalar value will be presented, including slicing, and various volume rendering techniques (ray casting, 3D texture-based volume rendering in OpenGL, cell sorting and projection). Contour curves and surfaces will also be discussed.
- Basic Vector Field Visualization A variety of techniques for the visualization of vector fields, i.e., vector-valued functions of the form [u(x,y), v(x,y)] and [u(x,y,z), v(x,y,z), w(x,y,z)] will be discussed. Algorithms that will be presented include the approximation and visualization of path, stream, streak, and time lines, surfaces, and tubes, as well as texture-based and glyph-based methods. Tensor visualization will also be briefly discussed. Optional topics:
- Molecular visualization: The techniques for visualizing atoms and bonds, and special glyphs for representing protein structures may be discussed.
- Animation: Methods for producing animated image sequences for visualizing time varying data, and for interpolating data in time as well as space, may be discussed.
- Tensor fields: The method of finding the principal components of a symmetric tensor may be discussed, as well as methods using them to visualize tensor fields.
- Information visualization: The distinction between scientific visualization of continuous quantitative data and information visualization of discrete or non-quantitative data and may be discussed, as well as a few examples of information visualization, for example, graph and/or tree visualization.
Alexandru Telea, Data Visualization: Principles and Practice. A K Peters, Ltd., 2008.
Potential Course Overlap