Summary. Time-varying scalar fields are produced by measurements or simulation of physical processes over time, and must be interpreted with the assistance of computational tools. A useful tool in interpreting the data is graphical visualization, often through level sets, or isocontours of a continuous function derived from the data. In this paper we survey isocontour based visualization techniques for time-varying scalar fields. We focus on techniques that aid selection of meaningful isocontours, and algorithms to extract chosen isocontours. Physical processes that are measured over time, or that are modeled and simulated on a computer, can produce large amounts of time-varying data that must be interpreted with the assistance of computational tools. Such data arises in a wide variety of studies including computational fluid dynamics [15] , oceanography [6], medical imaging [60] , and climate modeling [46] . The data typically consists of finitely many points in space-time and measured or computed values for each point. Often the values are scalar, with perhaps several scalar values for each sample point. E.g: Pressure, temperature, density. A study of motion or velocity of some kind will result in vector-valued data. In this paper, we focus on scalar-valued data, often called scalar fields. Irrespective of how the points are sampled, we can connect them into a mesh and interpolate the values to obtain a continuous function over the entire domain. Piecewise-linear interpolation is common for large amounts of data, because of its relative ease; multilinear interpolation is also used for regular grids. The goal is to understand the data, usually by exploring it for important features. A medical researcher might be interested in tumors, while a climatologist might be interested in regions of high pressure. Because humans possess a highly developed visual system, transforming the data into images and movies that can be displayed, and providing the scientist with tools to control them can be a powerful visualization method [47] . Popular techniques employed to create such visualizations are direct volume rendering, slicing, and isocontouring. Direct volume rendering employs two classes of algorithms to display all the data: imagespace projection and volume-space projection. In image-space projection algorithms we cast
We focus on scalar fields, where many feature definitions are based on isosurfaces REF .
Isocontour based Visualization of Time-varying Scalar Fields
Mathematical Foundations of Scientific Visualization, Computer Graphics, and Massive Data Exploration
Computer Science