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Leith Casey Leedom

dblp:99/1241 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1993
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1Human-computer interaction and ubiquitous computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Visualization and visual analytics · 56% Visual content generation and editing · 44%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics › flow visualization
line integral convolution
0.011993
Imaging vector fields using line integral convolution · SIGGRAPH 1993
Visual content generation and editing
texture synthesis
0.011993
Imaging vector fields using line integral convolution · SIGGRAPH 1993
Visualization and visual analytics › scientific visualization › field visualization
vector field visualization
0.011993
Imaging vector fields using line integral convolution · SIGGRAPH 1993

Methods — techniques the papers use, named apart from their topics

linear filtering · 0.0curvilinear filtering · 0.0
YearPublicationVenuePosition
1993 Imaging vector fields using line integral convolution
abstract
Imaging vector fields has applications in science, art, image processing and special effects. An effective new approach is to use linear and curvilinear filtering techniques to locally blur textures along a vector field. This approach builds on several previous texture generation and filtering techniques[8, 9, 11, 14, 15, 17, 23]. It is, however, unique because it is local, one-dimensional and independent of any predefined geometry or texture. The technique is general and capable of imaging arbitrary two- and three-dimensional vector fields. The local one-dimensional nature of the algorithm lends itself to highly parallel and efficient implementations. Furthermore, the curvilinear filter is capable of rendering detail on very intricate vector fields. Combining this technique with other rendering and image processing techniques ? like periodic motion filtering ? results in richly informative and striking images. The technique can also produce novel special effects.
Brian Cabral, Leith Casey Leedom
SIGGRAPH2