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Gary G. Gu

dblp:182/4738 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1991
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 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.

Computer graphics and multimedia
1 paper
Computational photography and imaging · 50% Image and video processing · 50%
Artificial intelligence
1 paper
3D vision · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational science and engineering · 100%

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

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision › 3d reconstruction
surface reconstruction		 0.011991
Boundary element methods for solving Poisson equations in computer vision problems · CVPR 1991
Image and video processing › motion estimation
optical flow		 0.011991
Boundary element methods for solving Poisson equations in computer vision problems · CVPR 1991
Computational photography and imaging › shape and reflectance estimation
shape from shading		 0.011991
Boundary element methods for solving Poisson equations in computer vision problems · CVPR 1991
Computational science and engineering › numerical solution of differential equations
boundary element method		 0.011991
Boundary element methods for solving Poisson equations in computer vision problems · CVPR 1991
Computational science and engineering
numerical analysis		 0.011991
Boundary element methods for solving Poisson equations in computer vision problems · CVPR 1991

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

finite element method · 0.0boundary element method · 0.0
YearPublicationVenuePosition
1991 Boundary element methods for solving Poisson equations in computer vision problems
abstract
The boundary element method (BEM) for solving Poisson's equations is described. Issues in BEM, such as Green's functions, boundary conditions, evaluation of improper integrals, and continuity up to first derivative of solution functions, are discussed. BEM is compared with FEM, the finite element method, in terms of storage and time complexity. The authors discuss application to vision: height from gradient; shape from shading; surface interpolation; brightness based stereo matching; and the optical flow problem. Brief mention is made of some early experimental results on synthetic images.>
Gary G. Gu, Michael A. Gennert
 CVPR1