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How hard is 3-view triangulation really?

Stewenius, Henrik LU ; Schaffalitzky, F and Nister, D (2005) IEEE International Conference on Computer Vision, 2005 p.686-693
Abstract
We present a solution for optimal triangulation in three views. The solution is guaranteed to find the optimal solution because it computes all the stationary points of the (maximum likelihood) objective function. Internally, the solution is found by computing roots of multivariate polynomial equations, directly solving the conditions for stationarity. The solver makes use of standard methods from computational commutative algebra to convert the root-finding problem into a 47
Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
scene geometry, image motion analysis, nonsymmetric eigenproblem, root-finding problem, computational commutative algebra, multivariate polynomial equation, maximum likelihood objective function, 3-view triangulation, optimal triangulation
host publication
Proceedings. Tenth IEEE International Conference on Computer Vision
pages
686 - 693
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
IEEE International Conference on Computer Vision, 2005
conference location
Beijing, China
conference dates
2005-10-17 - 2005-10-21
external identifiers
  • wos:000233155100089
  • scopus:33745968244
ISBN
0-7695-2334-X
DOI
10.1109/ICCV.2005.115
language
English
LU publication?
yes
id
e68f971b-e24e-4a96-89f1-ac6be6117236 (old id 616506)
date added to LUP
2016-04-04 12:23:20
date last changed
2022-01-29 23:19:38
@inproceedings{e68f971b-e24e-4a96-89f1-ac6be6117236,
  abstract     = {{We present a solution for optimal triangulation in three views. The solution is guaranteed to find the optimal solution because it computes all the stationary points of the (maximum likelihood) objective function. Internally, the solution is found by computing roots of multivariate polynomial equations, directly solving the conditions for stationarity. The solver makes use of standard methods from computational commutative algebra to convert the root-finding problem into a 47}},
  author       = {{Stewenius, Henrik and Schaffalitzky, F and Nister, D}},
  booktitle    = {{Proceedings. Tenth IEEE International Conference on Computer Vision}},
  isbn         = {{0-7695-2334-X}},
  keywords     = {{scene geometry; image motion analysis; nonsymmetric eigenproblem; root-finding problem; computational commutative algebra; multivariate polynomial equation; maximum likelihood objective function; 3-view triangulation; optimal triangulation}},
  language     = {{eng}},
  pages        = {{686--693}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{How hard is 3-view triangulation really?}},
  url          = {{http://dx.doi.org/10.1109/ICCV.2005.115}},
  doi          = {{10.1109/ICCV.2005.115}},
  year         = {{2005}},
}