Chapter 7: Tensor Visualization
Prerequisites: These projects do require a good understanding of the data representation techniques described in Chapter 3, and a basic understanding of OpenGL graphics (Chapter 2). Furthermore, they do require a good level of programming in C/C++ or a similar programming language, and a good understanding of numerical techniques such as vector-field integration and principal component analysis (PCA).
Aims: The provided projects are intended to test the students' ability to design and implement correct and efficient algorithms for tensor visualization. The focus here is on the interplay of data structures and algorithms used to
- represent 3D tensor datasets;
- compute tensor metrics, such as eigenvalues, eigenvectors, and anisotropy measures
- construct geometric abstractions for visualizing these metrics, such as slice planes, isosurfaces, and (hyper)streamlines
- render these abstractions using suitable OpenGL techniques.