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• W2150150409 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 well on arbitrary video sequences." @default.
• W2150150409 created "2016-06-24" @default.
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• W2150150409 date "2006-08-01" @default.
• W2150150409 modified "2023-10-17" @default.
• W2150150409 title "Using the low-resolution properties of correlated images to improve the computational efficiency of eigenspace decomposition" @default.
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• W2150150409 doi "https://doi.org/10.1109/tip.2006.875231" @default.
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