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G. Thomas Finnigan

dblp:87/2030 · DBLP profile ↗
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4ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 4

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
4 papers
Geometric modeling and processing · 100%

Topics — the 7 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Geometric modeling and processing › subdivision surfaces
catmull-clark subdivision
0.212016
G1 non-uniform Catmull-Clark surfaces · ACM Trans. Graph. 2016
Geometric modeling and processing › computer-aided design › computer-aided geometric design › surface continuity
g1 continuity
0.212016
G1 non-uniform Catmull-Clark surfaces · ACM Trans. Graph. 2016
Geometric modeling and processing
subdivision surfaces
0.212016
G1 non-uniform Catmull-Clark surfaces · ACM Trans. Graph. 2016
Geometric modeling and processing › computer-aided design › computer-aided geometric design
surface continuity
0.212016
G1 non-uniform Catmull-Clark surfaces · ACM Trans. Graph. 2016
Geometric modeling and processing › shape modeling › parametric modeling
spline surfaces
0.122008
Watertight trimmed NURBS · ACM Trans. Graph. 2008
T-spline simplification and local refinement · ACM Trans. Graph. 2004
Geometric modeling and processing › shape modeling › parametric modeling › spline surfaces
t-spline
0.122008
Watertight trimmed NURBS · ACM Trans. Graph. 2008
T-spline simplification and local refinement · ACM Trans. Graph. 2004
Geometric modeling and processing › solid modeling
boundary representation
0.112019
Generative Design Conversion to Editable and Watertight Boundary Representation · Comput. Aided Des. 2019

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

refinement rules · 0.2eigen polyhedron · 0.2
YearPublicationVenuePosition
2019 Generative Design Conversion to Editable and Watertight Boundary Representation
Martin Marinov, Marco Amagliani, Tristan Barback, Jean Flower, Stephen A. Barley, Suguru Furuta, Peter Charrot, Iain Henley, Nanda Santhanam, G. Thomas Finnigan, Siavash Meshkat, Justin Hallet, Maciej Sapun, Pawel Wolski
Comput. Aided Des.10
2016 G1 non-uniform Catmull-Clark surfaces
abstract
This paper develops new refinement rules for non-uniform Catmull-Clark surfaces that produce G 1 extraordinary points whose blending functions have a single local maximum. The method consists of designing an "eigen polyhedron" in R 2 for each extraordinary point, and formulating refinement rules for which refinement of the eigen polyhedron reduces to a scale and translation. These refinement rules, when applied to a non-uniform Catmull-Clark control mesh in R 3 , yield a G 1 extraordinary point.
Xin Li 0021, G. Thomas Finnigan, Thomas W. Sederberg
ACM Trans. Graph.2
2008 Watertight trimmed NURBS
abstract
This paper addresses the long-standing problem of the unavoidable gaps that arise when expressing the intersection of two NURBS surfaces using conventional trimmed-NURBS representation. The solution converts each trimmed NURBS into an untrimmed T-Spline, and then merges the untrimmed T-Splines into a single, watertight model. The solution enables watertight fillets of NURBS models, as well as arbitrary feature curves that do not have to follow iso-parameter curves. The resulting T-Spline representation can be exported without error as a collection of NURBS surfaces.
Thomas W. Sederberg, G. Thomas Finnigan, Xin Li 0021, Heather Ipson
ACM Trans. Graph.2
2004 T-spline simplification and local refinement
abstract
A typical NURBS surface model has a large percentage of superfluous control points that significantly interfere with the design process. This paper presents an algorithm for eliminating such superfluous control points, producing a T-spline. The algorithm can remove substantially more control points than competing methods such as B-spline wavelet decomposition. The paper also presents a new T-spline local refinement algorithm and answers two fundamental open questions on T-spline theory.
Thomas W. Sederberg, David L. Cardon, G. Thomas Finnigan, Nicholas S. North, Jianmin Zheng, Tom Lyche
ACM Trans. Graph.3