DocumentCode :
1863924
Title :
A very fast procedure to calculate the smallest singular value
Author :
Gerardo de la Fraga, Luis
Author_Institution :
Comput. Sci. Dept., Cinvestav, Mexico City, Mexico
fYear :
2015
fDate :
4-7 Jan. 2015
Firstpage :
1
Lastpage :
4
Abstract :
The optimization problem of estimate a vector x such that minimize ∥Ax∥ subject to ∥x∥ = 1, where A is a m×n matrix, is frequently found in computer vision. The solution of this problem is the right singular vector associated to the the smallest singular value. This problem must be solved very fast, for example, in real time applications as augmented reality environments are. It is show in this work that the old procedure to calculate directly the smallest singular value and to use one inverse iteration to calculate its associated singular vector is a faster procedure, compared with the state of the art algorithms to calculate the SVD, with relatively small square matrices.
Keywords :
computer vision; optimisation; singular value decomposition; vectors; SVD; computer vision; inverse iteration; matrices; optimization problem; singular value decomposition; singular vector; smallest singular value calculation; vector estimation; Cameras; Computer vision; Eigenvalues and eigenfunctions; Matrix decomposition; Solid modeling; Symmetric matrices; Vectors; Computer vision; singular value decomposition; singular value estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Pattern Recognition (ICAPR), 2015 Eighth International Conference on
Conference_Location :
Kolkata
Type :
conf
DOI :
10.1109/ICAPR.2015.7050656
Filename :
7050656
Link To Document :
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