Paper Info
Title
Generalized Hyper-cylinders: a Mechanism for Modeling and Visualizing N-D Objects
Abstract
The display of surfaces and solids has usually been restricted to the domain of scientific visual- ization; however, little work has been done on the visualization of surfaces and solids of dimen- sionality higher than three or four. Indeed, most high-dimensional visualization focuses on the display of data points. However, the ability to eectively model and visualize higher dimensional objects such as clusters and patterns would be quite useful in studying their shapes, relation- ships, and changes over time. In this paper we describe a method for the description, extraction, and visualization of N-dimensional surfaces and solids. The approach is to extend generalized cylinders, an object representation used in geometric modeling and computer vision, to arbitrary dimensionality, resulting in what we term Generalized Hyper-cylinders (GHCs). A basic GHC consists of two N-dimensional hyper-spheres connected by a hyper-cylinder whose shape at any point along the cylinder is determined by interpolating between the endpoint shapes. More com- plex GHCs involve alternate cross-section shapes and curved spines connecting the ends. Several algorithms for constructing or extracting GHCs from multivariate data sets are proposed. Once extracted, the GHCs can be visualized using a variety of projection techniques and methods to convey cross-section shapes. 1998 ACM Subject Classification I.3.5 Computational Geometry and Object Modeling
Year
Venue
Keywords
2010
Scientific Visualization: Advanced Concepts
cluster visualization,and phrases n-dimensional visualization,geometric model,cross section,multivariate data,object model,scientific visualization,computer vision
Field
DocType
Citations 
Data point,Computer graphics (images),Visualization,Computer science,Computational geometry,Interpolation,Geometric modeling,Object model,Curse of dimensionality,Scientific visualization
Conference
0
PageRank 
References 
Authors
0.34
9
2
Name
Order
Citations
PageRank
Matthew O. Ward11757189.48
Zhenyu Guo251239.61