Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/116359
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dc.contributor.authorBrooks, M.J.-
dc.contributor.authorChojnacki, W.-
dc.contributor.authorvan den Hengel, A.-
dc.contributor.authorBaumela, L.-
dc.contributor.editorBurkhardt, H.-
dc.contributor.editorNeumann, B.-
dc.date.issued1998-
dc.identifier.citationLecture Notes in Artificial Intelligence, 1998 / Burkhardt, H., Neumann, B. (ed./s), vol.1406, pp.281-295-
dc.identifier.isbn3540645691-
dc.identifier.isbn9783540645696-
dc.identifier.issn0302-9743-
dc.identifier.issn1611-3349-
dc.identifier.urihttp://hdl.handle.net/2440/116359-
dc.description.abstractRobust techniques are developed for determining structure from motion in the uncalibrated case. The structure recovery is based on previous work [7] in which it was shown that a camera undergoing unknown motion and having an unknown, and possibly varying, focal length can be self-calibrated via closed-form expressions in the entries of two matrices derivable from an instantaneous optical flow field. Critical to the recovery process is the obtaining of accurate numerical estimates, up to a scalar factor, of these matrices in the presence of noisy optical flow data. We present techniques for the determination of these matrices via least-squares methods, and also a way of enforcing a dependency constraint that is imposed on these matrices. A method for eliminating outlying flow vectors is also given. Results of experiments with real-image sequences are presented that suggest that the approach holds promise.-
dc.description.statementofresponsibilityMichael J. Brooks, Wojciech Chojnacki, Anton van den Hengel, Luis Baumela-
dc.language.isoen-
dc.publisherSpringer-
dc.relation.ispartofseriesLecture Notes in Computer Science; 1406-
dc.rights© Springer-Verlag Berlin Heidelberg 1998-
dc.source.urihttps://doi.org/10.1007/BFb0055655-
dc.titleRobust techniques for the estimation of structure from motion in the uncalibrated case-
dc.typeConference paper-
dc.contributor.conference5th European Conference on Computer Vision (ECCV'98) (2 Jun 1998 - 6 Jun 1998 : Freiburg, Germany)-
dc.identifier.doi10.1007/BFb0055673-
pubs.publication-statusPublished-
dc.identifier.orcidChojnacki, W. [0000-0001-7782-1956]-
dc.identifier.orcidvan den Hengel, A. [0000-0003-3027-8364]-
Appears in Collections:Aurora harvest 3
Australian Institute for Machine Learning publications
Computer Science publications

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