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Matthew He

dblp:91/2706 · DBLP profile ↗
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4ranked-venue papers
1as first author
0since 2021 · last 2011
0000-0002-7918-621XORCID · corroborated

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

Artificial intelligence and machine learning · 2Systems, architecture and hardware · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1Applied, interdisciplinary, general and emerging computing · 1

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 · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 100%

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

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision › motion estimation
motion parameter estimation
0.011994
Determination of motion parameters and estimation of point correspondences in small nonrigid deformations · CVPR 1994
Computer vision › 3D vision › feature matching
point correspondence
0.011994
Determination of motion parameters and estimation of point correspondences in small nonrigid deformations · CVPR 1994
Medical and health informatics
cardiac image analysis
0.011994
Determination of motion parameters and estimation of point correspondences in small nonrigid deformations · CVPR 1994

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

range image analysis · 0.0differential geometry · 0.0
YearPublicationVenuePosition
2011 Foreword
Matthew He, Zhengbing Hu
J. Supercomput.1
2009 Irreplaceable Amino Acids and Reduced Alphabets in Short-Term and Directed Protein Evolution
Miguel A. Jiménez-Montaño, Matthew He
ISBRA2
2003 3D nonrigid motion analysis under small deformations
Chandra Kambhamettu, Dmitry B. Goldgof, Matthew He, Pavel Laskov
Image Vis. Comput.3
1994 Determination of motion parameters and estimation of point correspondences in small nonrigid deformations
abstract
Recovery of motion parameters and point correspondences is a fundamental problem in computer vision. Although a great deal of research has been done in solving rigid motion, nonrigid motion analysis has only recently been addressed and is gaining interest due to its wide range of applications. This paper introduces a novel method for estimating motion parameters and point correspondences between surfaces under small nonrigid deformations. It uses the changes in differential geometric properties of surface under motion. Simulations are performed by generating nonrigid motion on an ellipsoidal data to illustrate performance and accuracy of derived algorithms, Then, the algorithm is tested on the sequence of facial range images. The motion parameters generated by the algorithm has also been used do detect the abnormality in cardiac images.>
Chandra Kambhamettu, Dmitry B. Goldgof, Matthew He
CVPR3