Repository logo
 

Fast eigenspace decomposition of correlated images

Date

1998

Authors

Balakrishnan, Venkataramanan, author
Maciejewski, Anthony A., author
Chang, C-Y., author
IEEE, publisher

Journal Title

Journal ISSN

Volume Title

Abstract

We 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.

Description

Rights Access

Subject

object recognition
matrix algebra
eigenvalues and eigenfunctions
computer vision

Citation

Associated Publications