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Fast eigenspace decomposition of correlated images

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dc.contributor.authorBalakrishnan, Venkataramanan, author
dc.contributor.authorMaciejewski, Anthony A., author
dc.contributor.authorChang, C-Y., author
dc.contributor.authorIEEE, publisher
dc.date.accessioned2007-01-03T06:17:10Z
dc.date.available2007-01-03T06:17:10Z
dc.date.issued1998
dc.description.abstractWe present a computationally efficient algorithm for the eigenspace decomposition of correlated images. Our approach is motivated by the fact that for a planar rotation of a two-dimensional image, analytical expressions can be given for the eigendecomposition, based on the theory of circulant matrices. These analytical expressions turn out to be good first approximations of the eigendecomposition, even for three-dimensional objects rotated about a single axis. We use this observation to automatically determine the dimension of the subspace required to represent an image with a guaranteed user-specified accuracy, as well as to quickly compute a basis for the subspace. Examples show that the algorithm performs very well on a range of test images composed of three-dimensional objects rotated about a single axis.
dc.description.sponsorshipThis work was supported by the Sze Tsao Chang Memorial Engineering Fund and by the Office of Naval Research under contract no. N00014-97-1-0540.
dc.format.mediumborn digital
dc.format.mediumproceedings (reports)
dc.identifier.bibliographicCitationChang, C-Y., A. A. Maciejewski, and V. Balakrishnan, Fast Eigenspace Decomposition of Correlated Images, 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems: Proceedings, Innovatiions in Theory, Practice, and Applications, October 13-17, 1998, Victoria, B.C., Canada: 7-12.
dc.identifier.urihttp://hdl.handle.net/10217/1223
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartofFaculty Publications
dc.rights©1998 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.subjectobject recognition
dc.subjectmatrix algebra
dc.subjecteigenvalues and eigenfunctions
dc.subjectcomputer vision
dc.titleFast eigenspace decomposition of correlated images
dc.typeText

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