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Glenn A. Kramer

dblp:60/4493 · DBLP profile ↗
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8ranked-venue papers
5as first author
0since 2021 · last 1996
—ORCID · none

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

Artificial intelligence and machine learning · 5 · 3 first-authorGraphics, computer vision, multimedia, augmented reality and games · 4 · 2 first-authorSystems, architecture and hardware · 1 · 1 first-author

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
3 papers
Geometric modeling and processing · 100%
Artificial intelligence
2 papers
Planning, search and constraint satisfaction · 57% 3D vision · 43%

Topics — the 5 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Geometric modeling and processing › computer-aided design
assembly modeling
0.011996
Assembly modelling by geometric constraint satisfaction · Comput. Aided Des. 1996
Geometric modeling and processing
geometric constraint solving
0.011993
Solving geometric constraint systems a case study in kinematics · Comput. Aided Des. 1993
Computer vision › 3D vision › geometric reasoning
geometric constraint solving
0.011992
A Geometric Constraint Engine · Artif. Intell. 1992
Geometric modeling and processing › computer-aided design › computer-aided geometric design
geometric constraints
0.011990
Solving Geometric Constraint Systems · AAAI 1990
Geometric modeling and processing
kinematic analysis
0.011993
Solving geometric constraint systems a case study in kinematics · Comput. Aided Des. 1993
YearPublicationVenuePosition
1996 Assembly modelling by geometric constraint satisfaction
Ram Anantha, Glenn A. Kramer, Richard H. Crawford
Comput. Aided Des.2
1996 A Principled Approach Towards Symbolic Geometric Constraint Satisfaction
abstract
An important problem in geometric reasoning is to find the configuration of a collection of geometric bodies so as to satisfy a set of given constraints. Recently, it has been suggested that this problem can be solved efficiently by symbolically reasoning about geometry. This approach, called degrees of freedom analysis, employs a set of specialized routines called plan fragments that specify how to change the configuration of a set of bodies to satisfy a new constraint while preserving existing constraints. A potential drawback, which limits the scalability of this approach, is concerned with the difficulty of writing plan fragments. In this paper we address this limitation by showing how these plan fragments can be automatically synthesized using first principles about geometric bodies, actions, and topology.
Sanjay Bhansali, Glenn A. Kramer, Tim J. Hoar
J. Artif. Intell. Res.2
1994 Planning from First Principles for Geometric Constraint Satisfaction
Sanjay Bhansali, Glenn A. Kramer
AAAI2
1993 Solving geometric constraint systems a case study in kinematics
Glenn A. Kramer
Comput. Aided Des.1
1992 A Geometric Constraint Engine
Glenn A. Kramer
Artif. Intell.1
1992 Comments on Prolegomena e by Sacks and Doyle
Glenn A. Kramer
Comput. Intell.1
1990 Solving Geometric Constraint Systems
Glenn A. Kramer
AAAI1
1983 Employing Massive Parallelism in Digital ATPG Algorithms
Glenn A. Kramer
ITC1