K
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.
Papers
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Proceedings ArticleDOI
Free-form deformations with lattices of arbitrary topology
Ron MacCracken,Kenneth I. Joy +1 more
TL;DR: A new free-form deformation technique is presented that generalizes previous methods by allowing 3-dimensional deformation lattices of arbitrary topology to be defined, and thus a broader range of shape deformations can be generated.
Visualization and computer graphics
David S. Ebert,Charles Hansen,Georges-Pierre Bonneau,L. A. B. Gravir,Leila De Floriani,Kenneth I. Joy,Rick Parent,Hanspeter Pfister,Rüdiger Westerman,Henry Fuchs,E. Shaffer,M. Garland +11 more
Proceedings ArticleDOI
Multiresolution techniques for interactive texture-based volume visualization
TL;DR: This paper presents a multiresolution technique for interactive texture-based volume visualization of very large data sets that uses an adaptive scheme that renders the volume in a region-of-interest at a high resolution and the volume away from this region at progressively lower resolutions.
Journal ArticleDOI
Sound graphs: a numerical data analysis method for the blind.
Douglass L. Mansur,Douglass L. Mansur,Merra M. Blattner,Merra M. Blattner,Merra M. Blattner,Kenneth I. Joy,Kenneth I. Joy +6 more
TL;DR: To test the feasibility of using sound to represent graphs, a prototype system was developed and human factors experimenters were performed and it was discovered that mathematical concepts such as symmetry, monotonicity, and the slopes of lines could be determined quickly using sound.
Proceedings ArticleDOI
Construction of vector field hierarchies
TL;DR: This work presents a method for the hierarchical representation of vector fields based on iterative refinement using clustering and principal component analysis, and assumes no particular structure of the field, nor does it require any topological connectivity information.