Time-varying volumetric data arise in a variety of application domains, and thus several techniques for dealing with such data have been proposed in the literature. A time-varying dataset is typically modeled either as a collection of discrete snapshots of volumetric data, or as a four-dimensional dataset. This choice influences the operations that can be efficiently performed on such data. Here, we classify the various approaches to modeling time-varying scalar fields, and briefly describe them. Since most models of time-varying data have been abstracted from well-known approaches to volumetric data, we review models of volumetric data as well as schemes to accelerate isosurface extraction and discuss how these approaches have been applied to time-varying datasets. Finally, we discuss multi-resolution approaches which allow interactive processing and visualization of large time varying datasets. © 2008 Springer Berlin Heidelberg.
CITATION STYLE
Weiss, K., & De Floriani, L. (2008). Modeling and visualization approaches for time-varying volumetric data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5359 LNCS, pp. 1000–1010). https://doi.org/10.1007/978-3-540-89646-3_100
Mendeley helps you to discover research relevant for your work.