Analysis of eigendecomposition for sets of correlated images at different resolutions
Saitwal, Kishor ; Maciejewski, Anthony A. ; Roberts, Rodney G.
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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 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.