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dc.contributor.authorRING, DANIELen
dc.contributor.authorPITIE, FRANCOISen
dc.date.accessioned2010-04-29T15:54:43Z
dc.date.available2010-04-29T15:54:43Z
dc.date.createdSeptember 2-4en
dc.date.issued2009en
dc.date.submitted2009en
dc.identifier.citationD. Ring and F. Pitie, Feature-Assisted Sparse to Dense Motion Estimation using Geodesic Distances., IEEE Irish Machine Vision and Image Processing conference (IMVIP '09, Dublin, Ireland, September 2-4, IEEE, 2009, 7-12en
dc.identifier.otherYen
dc.descriptionPUBLISHEDen
dc.description.abstractLarge motion displacements in image sequences are still a problem for most motion estimation techniques. Progress in feature matching allows to establish robust correspondences between images for a sparse set of points. Recent works have attempted to use this sparse information to guide the dense motion field estimation. We propose to achieve this in an extended motion estimation framework, which integrates information about the geodesic distance to the sparse features. Results show that by considering a handful of these feature matches, the geodesic distance is able to propagate the information efficiently.en
dc.format.extent7-12en
dc.language.isoenen
dc.publisherIEEEen
dc.rightsYen
dc.subjectLocal features Motion vector estimation Large displacement Geodesic distance candidate selectionen
dc.titleFeature-Assisted Sparse to Dense Motion Estimation using Geodesic Distances.en
dc.title.alternativeIEEE Irish Machine Vision and Image Processing conference (IMVIP '09en
dc.typeConference Paperen
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/pitiefen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/dringen
dc.identifier.rssinternalid64073en
dc.identifier.urihttp://hdl.handle.net/2262/39299


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