DocumentCode :
3014815
Title :
Using Galois Theory to Prove Structure from Motion Algorithms are Optimal
Author :
Nistér, David ; Hartley, Richard ; Stewénius, Henrik
Author_Institution :
Microsoft Live Labs, Seattle
fYear :
2007
fDate :
17-22 June 2007
Firstpage :
1
Lastpage :
8
Abstract :
This paper presents a general method, based on Galois theory, for establishing that a problem can not be solved by a ´machine´ that is capable of the standard arithmetic operations, extraction of radicals (that is, m-th roots for any m), as well as extraction of roots of polynomials of degree smaller than n, but no other numerical operations. The method is applied to two well known structure from motion problems: five point calibrated relative orientation, which can be realized by solving a tenth degree polynomial [6], and L2-optimal two-view triangulation, which can be realized by solving a sixth degree polynomial [3]. It is shown that both these solutions are optimal in the sense that an exact solution intrinsically requires the solution of a polynomial of the given degree (10 or 6 respectively), and cannot be solved by extracting roots of polynomials of any lesser degree.
Keywords :
Galois fields; arithmetic; computer vision; polynomials; Galois theory; L2-optimal two-view triangulation; calibrated relative orientation; degree polynomial; motion algorithms; radicals extraction; standard arithmetic operations; Computer science; Digital arithmetic; Equations; Polynomials; Singular value decomposition; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on
Conference_Location :
Minneapolis, MN
ISSN :
1063-6919
Print_ISBN :
1-4244-1179-3
Electronic_ISBN :
1063-6919
Type :
conf
DOI :
10.1109/CVPR.2007.383089
Filename :
4270114
Link To Document :
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