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Analysis of eigendecomposition for sets of correlated images at different resolutions

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dc.contributor.authorSaitwal, Kishor, author
dc.contributor.authorMaciejewski, Anthony A., author
dc.contributor.authorRoberts, Rodney G., author
dc.contributor.authorIEEE, publisher
dc.date.accessioned2015-07-28T20:36:11Z
dc.date.available2015-07-28T20:36:11Z
dc.date.issued2004
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 gives the theoretical background for quantifying the effects of varying the resolution of images on the eigendecomposition that is computed from those images. A computationally efficient algorithm for this eigendecomposition is proposed using derived analytical expressions. Examples show that this algorithm performs very well on arbitrary video sequences.
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, Analysis of Eigendecomposition for Sets of Correlated Images at Different Resolutions, 2004 IEEE International Conference on Robotics and Automation: Proceedings, April 26-May 1, 2004, New Orleans, LA: 1393-1398.
dc.identifier.urihttp://hdl.handle.net/10217/1357
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartofFaculty Publications
dc.rights©2004 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.subjectcomputational complexity
dc.subjecteigenvalues and eigenfunctions
dc.subjectimage resolution
dc.subjectimage sequences
dc.subjectrobot vision
dc.subjectsingular value decomposition
dc.titleAnalysis of eigendecomposition for sets of correlated images at different resolutions
dc.typeText

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