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Kenneth I. Joy

Researcher at University of California, Davis

Publications -  228
Citations -  5476

Kenneth I. Joy is an academic researcher from University of California, Davis. The author has contributed to research in topics: Visualization & Data visualization. The author has an hindex of 38, co-authored 228 publications receiving 5241 citations. Previous affiliations of Kenneth I. Joy include University of California & Carl Albert State College.

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Proceedings ArticleDOI

Wavelet representation of contour sets

TL;DR: A new wavelet compression and multiresolution modeling approach for sets of contours (level sets) based on hierarchical polygon meshes with subdivision connectivity whose vertices are transformed into wavelet coefficients, which preserves contour topology in contrast to compression methods applied to the corresponding field function.
Journal ArticleDOI

Utilizing parametric hyperpatch methods for modeling and display of free-form solids

TL;DR: Methods of creating, modifying and visualizing free-form geometric models, by use of the B-spline hyperpatch, and the hyperpatch model, were introduced and the complexity of free- form solid object construction was found to be significantly simplified.
Book ChapterDOI

Visualization of swept hyperpatch solids

TL;DR: In this article, a method was given that refines the swept object into one or more hyperpatch objects, each of which can then be further refined into a set of B-spline boundary patches.
Proceedings ArticleDOI

Designers workbench: toward real-time immersive modeling

TL;DR: The Designers Workbench aims at closing this technology or 'digital gap' experienced by design and CAD engineers by transforming the classical design paradigm into its fully integrate digital and virtual analog allowing collaborative development in a semi- immersive virtual environment.

An Error-Controlled Octree Data Structure for Large-Scale Visualization

TL;DR: The fields of medical imaging, vector field visualization, flow simulation, and computational fluid dynamics (CFD) produce large data sets, which cannot be rendered in a reasonable amount of time because they are timeconsuming and intractable.