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Gary J. Balas

dblp:25/5066 · also Gary Balas · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 1996
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 2

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
Image and video processing · 100%

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

TopicWeightPapersLastEvidence papers
Image and video processing
motion estimation		 0.011996
Optical flow: a curve evolution approach · IEEE Trans. Image Process. 1996
Image and video processing › motion estimation
optical flow		 0.011996
Optical flow: a curve evolution approach · IEEE Trans. Image Process. 1996
Image and video processing › motion estimation › optical flow
variational optical flow		 0.011996
Optical flow: a curve evolution approach · IEEE Trans. Image Process. 1996

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

level set method · 0.0l1 minimization · 0.0curve evolution · 0.0
YearPublicationVenuePosition
1996 Optical flow: a curve evolution approach
abstract
A novel approach for the computation of optical flow based on an L (1) type minimization is presented. It is shown that the approach has inherent advantages since it does not smooth the flow-velocity across the edges and hence preserves edge information. A numerical approach based on computation of evolving curves is proposed for computing the optical flow field. Computations are carried out on a number of real image sequences in order to illustrate the theory as well as the numerical approach.
Arun Kumar 0009, Allen R. Tannenbaum, Gary J. Balas
 IEEE Trans. Image Process.3
1995 Optical flow: a curve evolution approach
abstract
A novel approach for the computation of optical flow based on an L/sup 1/ type minimization is presented. It is shown that the approach has inherent advantages since it does not smooth the flow-velocity across the edges and hence preserves edge information. A numerical approach based on computation of evolving curves is proposed for computing the optical flow field and results of experiments are presented.
Arun Kumar 0009, Allen R. Tannenbaum, Gary J. Balas
 ICIP (3)3