Saitwal, Kishor, authorMaciejewski, Anthony A., authorRoberts, Rodney G., authorIEEE, publisher2015-07-282015-07-282004Saitwal, Kishor, Anthony A. Maciejewski, and Rodney G. Roberts, Analysis of Eigendecomposition for Sets of Correlated Images at Different Resolutions, 2004 IEEE International Conference on Robotics and Automation: Proceedings, April 26-May 1, 2004, New Orleans, LA: 1393-1398.http://hdl.handle.net/10217/1357Eigendecomposition 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.born digitalproceedings (reports)eng©2004 IEEE.Copyright 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.computational complexityeigenvalues and eigenfunctionsimage resolutionimage sequencesrobot visionsingular value decompositionText