Modeling and Visualization Approaches for Time-Varying Volumetric Data

被引:0
|
作者
Weiss, Kenneth [1 ]
De Floriani, Leila [2 ]
机构
[1] Univ Maryland, Dept Comp Sci, College Pk, MD 20742 USA
[2] Univ Genoa, Dept Comp Sci, Genoa, Italy
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Time-varying volurnetric 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 in multi-resolution approaches which allow interactive processing and visualization of large time varying datasets.
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页码:1000 / +
页数:4
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