Linked Life Data

18237885

Source:http://linkedlifedata.com/resource/pubmed/id/18237885

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
10
pubmed:dateCreated
2008-2-1
pubmed:abstractText
An accurate optical flow estimation algorithm is proposed in this paper. By combining the three-dimensional (3D) structure tensor with a parametric flow model, the optical flow estimation problem is converted to a generalized eigenvalue problem. The optical flow can be accurately estimated from the generalized eigenvectors. The confidence measure derived from the generalized eigenvalues is used to adaptively adjust the coherent motion region to further improve the accuracy. Experiments using both synthetic sequences with ground truth and real sequences illustrate our method. Comparisons with classical and recently published methods are also given to demonstrate the accuracy of our algorithm.
pubmed:language
eng
pubmed:journal
pubmed:status
PubMed-not-MEDLINE
pubmed:issn
1057-7149
pubmed:author
pubmed:issnType
Print
pubmed:volume
12
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1170-80
pubmed:year
2003
pubmed:articleTitle
Accurate dense optical flow estimation using adaptive structure tensors and a parametric model.
pubmed:affiliation
Center for Autom. Res., Univ. of Maryland, College Park, MD 20742, USA. hyliu@cfar.umd.edu
pubmed:publicationType
Journal Article