Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/29483
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dc.contributor.authorBrooks, M.en
dc.contributor.authorChojnacki, W.en
dc.contributor.authorGawley, D.en
dc.contributor.authorVan Den Hengel, A.en
dc.date.issued2001en
dc.identifier.citationEighth IEEE International Conference on Computer Vision, 2001: pp. 302-308en
dc.identifier.isbn0769511430en
dc.identifier.urihttp://hdl.handle.net/2440/29483-
dc.description©2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en
dc.description.abstractMany parameter estimation methods used in computer vision are able to utilise covariance information describing the uncertainty of data measurements. This paper considers the value of this information to the estimation process when applied to measured image point locations. Covariance matrices are first described and a procedure is then outlined whereby covariances may be associated with image features located via a measurement process. An empirical study is made of the conditions under which covariance information enables generation of improved parameter estimates. Also explored is the extent to which the noise should be anisotropic and inhomogeneous if improvements are to be obtained over covariance-free methods. Critical in this is the devising of synthetic experiments under which noise conditions can be precisely controlled. Given that covariance information is, in itself, subject to estimation error tests are also undertaken to determine the impact of imprecise covariance information upon the quality of parameter estimates. Finally, an experiment is carried out to assess the value of covariances in estimating the fundamental matrix from real imagesen
dc.description.statementofresponsibilityBrooks, M.J. Chojnacki, W. Gawley, D. van den Hengel, A.en
dc.language.isoenen
dc.publisherIEEE COMPUTER SOCIETYen
dc.titleWhat value covariance information in estimating vision parameters?en
dc.typeConference paperen
dc.identifier.rmid0020012254en
dc.contributor.conferenceIEEE International Conference on Computer Vision (8th : 2001 : Vancouver, Canada)en
dc.identifier.doi10.1109/ICCV.2001.10029en
dc.publisher.placeLOS ALAMITOS, CALIFORNIA, USAen
dc.identifier.pubid60960-
pubs.library.collectionComputer Science publicationsen
pubs.verification-statusVerifieden
pubs.publication-statusPublisheden
dc.identifier.orcidChojnacki, W. [0000-0001-7782-1956]en
dc.identifier.orcidVan Den Hengel, A. [0000-0003-3027-8364]en
Appears in Collections:Computer Science publications

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