Level set methods, an important class of partial differential equation (PDE) methods, define dynamic surfaces implicitly as the level set (iso-surface) of a sampled, evolving nD function. This course is targeted for researchers interested in learning about level set methods, and their application to visualization. The course material will be presented by two recognized experts in the field, and will include introductory concepts, practical considerations and extensive details on a number of level set applications.
The course will be taught at an intermediate to advanced level. Therefore attendees should have a working knowledge of calculus, linear algebra, computer graphics and geometric modeling. Some familiarity with differential geometry, differential equations, numerical computing and image processing is strongly recommended, but not required.
The course will begin with preparatory material that introduces the concept of using deformable implicit models to solve problems in visualization. This will include the structure and behavior of the level set differential equation, as well as an introduction to level set software. This stage of the course will also describe the numerical methods, algorithms and data structures needed to implement level set methods. The second stage will describe in detail a number of level set visualization applications, e.g. volume dataset segmentation (including interactive segmentation on GPUs), and surface reconstruction from contours and point clouds.