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Using the low-resolution properties of correlated images to improve the computational efficiency of eigenspace decomposition

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dc.contributor.authorDraper, Bruce A., author
dc.contributor.authorRoberts, Rodney G., author
dc.contributor.authorMaciejewski, Anthony A., author
dc.contributor.authorSaitwal, Kishor, author
dc.contributor.authorIEEE, publisher
dc.date.accessioned2007-01-03T07:26:31Z
dc.date.available2007-01-03T07:26:31Z
dc.date.issued2006
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 a priori how this will affect the quality of the resulting eigendecomposition. The work presented here provides an analysis of how different resolution reduction techniques affect the eigendecomposition. A computationally efficient algorithm for calculating the eigendecomposition based on this analysis is proposed. Examples show that this algorithm performs well on arbitrary video sequences.
dc.description.sponsorshipThis work was supported by the National Imagery and Mapping Agency under Contract 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.mediumarticles
dc.identifier.bibliographicCitationSaitwal, Kishor, et al., Using the Low-Resolution Properties of Correlated Images to Improve the Computational Efficiency of Eigenspace Decomposition, IEEE Transactions on Image Processing 15, no. 8 (August 2006): 2376-2387.
dc.identifier.urihttp://hdl.handle.net/10217/620
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartofFaculty Publications
dc.rights©2006 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.subjectcomputer vision
dc.subjectcorrelation
dc.subjectdata compression
dc.subjecteigenspace
dc.subjectimage resolution
dc.subjectimage sampling
dc.subjectimage sequences
dc.subjectsingular value decomposition (SVD)
dc.subjectvideo coding
dc.titleUsing the low-resolution properties of correlated images to improve the computational efficiency of eigenspace decomposition
dc.typeText

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