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Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier6qtX3pFwXQZG2LgkFdY/MaSM9
Repositorysid.inpe.br/sibgrapi@80/2006/08.16.16.56
Last Update2006:08.16.16.56.46 administrator
Metadatasid.inpe.br/sibgrapi@80/2006/08.16.16.56.47
Metadata Last Update2020:02.19.03.17.45 administrator
Citation KeyStukeBartMota:2006:EsMuOr
TitleEstimation of Multiple Orientations and Multiple Motions in Multi-Dimensional Signals
FormatOn-line
Year2006
Date8-11 Oct. 2006
Access Date2021, Jan. 19
Number of Files1
Size386 KiB
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Author1 Stuke, Ingo
2 Barth, Erhardt
3 Mota, Cicero
Affiliation1 Institute for Signal Processing, University of Luebeck
2 Institute for Neuro- and Bioinformatics, University of L uebeck
3 Departamento de Matemática, Universidade Federal do Amazonas
EditorOliveira Neto, Manuel Menezes de
Carceroni, Rodrigo Lima
e-Mail Addresscicmota@gmail.com
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 19 (SIBGRAPI)
Conference LocationManaus
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
History2006-08-16 16:56:47 :: cicmota -> banon ::
2006-08-30 21:59:08 :: banon -> cicmota ::
2008-07-17 14:11:04 :: cicmota -> administrator ::
2009-08-13 20:38:12 :: administrator -> banon ::
2010-08-28 20:02:25 :: banon -> administrator ::
2020-02-19 03:17:45 :: administrator -> :: 2006
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Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Keywordsmultiple orientations, multiple motions, transparency, occlusion.
AbstractEstimation of multiple orientations in multi-dimensional signals is a strong non-linear problem. A solution form this problem is presented in two steps. First, it is linearized by introducing the so-called "mixed orientations parameters" as an unique, albeit implicit, descriptor of the orientations. Next, the non-linearities are solved in order to find the individual orientations. For two-dimensional signals, e.g., images, this decomposition step is solved by seeking for the roots of polynomials. For multi-dimensional signals, the decomposition problem is reduced to a cascade of decompositions problems in two dimensional signals and solved. Therefore, a full solution for the estimation of any numbers of orientations in any dimension is achieved.
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data URLhttp://urlib.net/rep/6qtX3pFwXQZG2LgkFdY/MaSM9
zipped data URLhttp://urlib.net/zip/6qtX3pFwXQZG2LgkFdY/MaSM9
Languageen
Target FileMotaC_EstimationOrientationMotion.pdf
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Host Collectionsid.inpe.br/banon/2001/03.30.15.38
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