Anthony J. Pollitt

dblp:32/7052 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2009
—ORCID · none

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

Artificial intelligence and machine learning · 2 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 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.

Artificial intelligence
1 paper
3D vision · 87% Image recognition and object detection · 13%
Computer graphics and multimedia
1 paper
Geometric modeling and processing · 100%

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

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision
3d shape representation
0.112009
Transitions of the 3D Medial Axis under a One-Parameter Family of Deformations · IEEE Trans. Pattern Anal. Mach. Intell. 2009
Computer vision › 3D vision › 3d shape representation › skeleton representation
medial axis representation
0.112009
Transitions of the 3D Medial Axis under a One-Parameter Family of Deformations · IEEE Trans. Pattern Anal. Mach. Intell. 2009
Geometric modeling and processing › shape analysis
medial axis
0.012004
Consistency Conditions on the Medial Axis · ECCV (2) 2004
Computer vision › Image recognition and object detection
shape recognition
0.012009
Transitions of the 3D Medial Axis under a One-Parameter Family of Deformations · IEEE Trans. Pattern Anal. Mach. Intell. 2009

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

one-parameter deformation family · 0.1contact order analysis · 0.1
YearPublicationVenuePosition
2009 Transitions of the 3D Medial Axis under a One-Parameter Family of Deformations
abstract
The instabilities of the medial axis of a shape under deformations have long been recognized as a major obstacle to its use in recognition and other applications. These instabilities, or transitions, occur when the structure of the medial axis graph changes abruptly under deformations of shape. The recent classification of these transitions in 2D for the medial axis and for the shock graph was a key factor in the development of an object recognition system where the classified instabilities were utilized to represent deformation paths. The classification of generic transitions of the 3D medial axis could likewise potentially lead to a similar representation in 3D. In this paper, these transitions are classified by examining the order of contact of spheres with the surface, leading to an enumeration of possible transitions which are then examined on a case-by-case basis. Some cases are ruled out as never occurring in any family of deformations, while others are shown to be nongeneric in a one-parameter family of deformations. Finally, the remaining cases are shown to be viable by developing a specific example for each. Our work is inspired by that of Bogaevsky, who obtained the transitions as part of an investigation of viscosity solutions of Hamilton-Jacobi equations. Our contribution is to give a more down-to-earth approach, bringing this work to the attention of the computer vision community, and to provide explicit constructions for the various transitions using simple surfaces. We believe that the classification of these transitions is vital to the successful regularization of the medial axis in its use in real applications.
Peter J. Giblin, Benjamin B. Kimia, Anthony J. Pollitt
IEEE Trans. Pattern Anal. Mach. Intell.3
2004 Consistency Conditions on the Medial Axis
Anthony J. Pollitt, Peter J. Giblin, Benjamin B. Kimia
ECCV (2)1