DocumentCode :
414275
Title :
Analysis of eigendecomposition for sets of correlated images at different resolutions
Author :
Saitwal, Kishor ; Maciejewski, Anthony A. ; Roberts, Rodney G.
Author_Institution :
Dept. of Electr. & Comput. Eng., Colorado State Univ., Fort Collins, CO, USA
Volume :
2
fYear :
2004
fDate :
April 26-May 1, 2004
Firstpage :
1393
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 becomes prohibitively expensive when dealing with very high resolution images. Reducing the resolution of the images reduces the computational expense, it is not known how this affects 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.
Keywords :
computational complexity; eigenvalues and eigenfunctions; image resolution; image sequences; robot vision; singular value decomposition; computational complexity; computer vision; correlated images; eigendecomposition; high resolution images; robotics; video sequences; Algorithm design and analysis; Application software; Computer vision; Face detection; Identity-based encryption; Image analysis; Image processing; Image resolution; Pixel; Singular value decomposition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 2004. Proceedings. ICRA '04. 2004 IEEE International Conference on
ISSN :
1050-4729
Print_ISBN :
0-7803-8232-3
Type :
conf
DOI :
10.1109/ROBOT.2004.1308019
Filename :
1308019
Link To Document :
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