Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/55342
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dc.contributor.authorSchindler, K.-
dc.contributor.authorSuter, D.-
dc.contributor.editorSchmid, C.-
dc.contributor.editorSoatto, S.-
dc.contributor.editorTomasi, C.-
dc.date.issued2005-
dc.identifier.citationProceedings IEEE Conference in Computer Vision and Pattern Recognition, CVPR 2005: www1-8-
dc.identifier.isbn0769523722-
dc.identifier.isbn9780769523729-
dc.identifier.issn1063-6919-
dc.identifier.urihttp://hdl.handle.net/2440/55342-
dc.description.abstractMulti-body structure-and-motion (MSaM) is the problem to establish the multiple-view geometry of several views of a 3D scene taken at different times, where the scene consists of multiple rigid objects moving relative to each other. We examine the case of two views. The setting is the following: given are a set of corresponding image points in two images, which originate from an unknown number of moving scene objects, each giving rise to a motion model. Furthermore, the measurement noise is unknown, and there are a number of gross errors, which are outliers to all models. The task to find an optimal set of motion models for the measurements is solved through Monte-Carlo sampling, careful statistical analysis of the data and simultaneous selection of multiple motion models.-
dc.description.statementofresponsibilityKonrad Schindler and David Suter-
dc.language.isoen-
dc.publisherIEEE-
dc.relation.ispartofseriesIEEE Conference on Computer Vision and Pattern Recognition-
dc.source.urihttp://dx.doi.org/10.1109/cvpr.2005.355-
dc.titleTwo-view multibody structure-and-motion with outliers-
dc.typeConference paper-
dc.contributor.conferenceIEEE Computer Society Conference on Computer Vision and Pattern Recognition (18th : 2005 : San Diego, CA, U.S.A.)-
dc.identifier.doi10.1109/CVPR.2005.355-
dc.publisher.placeOnline-
pubs.publication-statusPublished-
dc.identifier.orcidSuter, D. [0000-0001-6306-3023]-
Appears in Collections:Aurora harvest
Computer Science publications

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