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A comparison of eigendecomposition for sets of correlated images at different resolutions

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dc.contributor.authorRoberts, Rodney G., author
dc.contributor.authorMaciejewski, Anthony A., author
dc.contributor.authorSaitwal, Kishor, author
dc.contributor.authorIEEE, publisher
dc.date.accessioned2007-01-03T04:44:06Z
dc.date.available2007-01-03T04:44:06Z
dc.date.issued2003
dc.description.abstractEigendecomposition is a common technique that is performed on sets of correlated images in a number of computer vision and robotics applications. Unfortunately, the computation of an eigendecomposition can become prohibitively expensive when dealing with very high resolution images. While reducing the resolution of the images will reduce the computational expense, it is not known how this will affect the quality of the resulting eigendecomposition. The work presented here proposes a framework for quantifying the effects of varying the resolution of images on the eigendecomposition that is computed from those images. Preliminary results show that an eigendecomposition from low-resolution images may be nearly as effective in some applications as those from high-resolution images.
dc.description.sponsorshipThis work was supported by the National Imagery and Mapping Agency under contract no. NMA201-00-1-1003 and through collaborative participation in the Robotics Consortium sponsored by the U. S. Army Research Laboratory under the Collaborative Technology Alliance Program, Cooperative Agreement DAAD19-01-2-0012.
dc.format.mediumborn digital
dc.format.mediumproceedings (reports)
dc.identifier.bibliographicCitationSaitwal, Kishor, Anthony A. Maciejewski, and Rodney G. Roberts, A Comparison of Eigendecomposition for Sets of Correlated Images at Different Resolutions, 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003), October 27-31, 2003, Las Vegas, Nevada, Proceedings: 1011-1017.
dc.identifier.urihttp://hdl.handle.net/10217/1354
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartofFaculty Publications
dc.rights©2003 IEEE.
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectimage resolution
dc.subjecteigenvalues and eigenfunctions
dc.subjectcomputer vision
dc.subjectmatrix algebra
dc.subjectsingular value decomposition
dc.titleA comparison of eigendecomposition for sets of correlated images at different resolutions
dc.typeText

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