Fast eigenspace decomposition of correlated images using their low-resolution properties
Date
2004
Authors
Saitwal, Kishor, author
Maciejewski, Anthony A., author
Roberts, Rodney G., author
IEEE, publisher
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Abstract
Eigendecomposition 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 very well on arbitrary video sequences.
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Subject
correlation methods
decomposition
eigenvalues and eigenfunctions
image resolution