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dc.contributor.authorSellent, Anita
dc.contributor.authorEisemann, Martin
dc.contributor.authorMagnor, Marcus
dc.contributor.editorSkala, Václav
dc.identifier.citationJournal of WSCG. 2011, vol. 19, no. 1-3, p. 1-8.en
dc.identifier.issn1213–6972 (hardcopy)
dc.identifier.issn1213–6980 (CD-ROM)
dc.identifier.issn1213–6964 (on-line)
dc.description.abstractWe present a robust feature matching approach that considers features from more than two images during matching. Traditionally, corners or feature points are matched between pairs of images. Starting from one image, corresponding features are searched in the other image. Yet, often this two-image matching is only a subproblem and actually robust matches over multiple views and/ or images acquired at several instants in time are required. In our feature matching approach we consider the multi-view video data modality and find matches that are consistent in three images. Requiring neither calibrated nor synchronized cameras, we are able to reduce the percentage of wrongly matched features considerably. We evaluate the approach for different feature detectors and their natural descriptors and show an application of our improved matching approach for optical flow calculation on unsynchronized stereo sequences.en
dc.format8 s.cs
dc.publisherVáclav Skala - UNION Agencycs
dc.relation.ispartofseriesJournal of WSCGen
dc.rights© Václav Skala - UNION Agencycs
dc.subjectpárování význačných bodůcs
dc.subjectodhad pohybucs
dc.subjectmulti-view videocs
dc.titleRobust feature point matching in general multi-imageen
dc.subject.translatedfeature point matchingen
dc.subject.translatedmotion estimationen
dc.subject.translatedmulti-view videoen
Appears in Collections:Number 1-3 (2011)

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Please use this identifier to cite or link to this item: http://hdl.handle.net/11025/1246

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