A Triangulation Method in 3D Reconstruction from Image Sequences

Author

Mandun, Zhang ; Lichao, Qi ; Guodong, Cui ; Ming, Yu

Author_Institution

Coll. of Comput. Sci. & Software, Hebei Univ. of Technol., Tianjin, China

fYear

2009

fDate

1-3 Nov. 2009

Firstpage

306

Lastpage

308

Abstract

There are several approaches invented for solving the triangulation problem in computer vision. Most of them are not projective-invariant, which is very important in 3D reconstruction. Therefore, we propose the method in this paper to solve the problem. Instead of solving high order equation, we introduce second-order Lagrange multiplier. We get the result by iterative, and therefore the result will not be trapped in some local minima. We show extensive results on synthetic data to validate our algorithm.

Keywords

computer vision; image reconstruction; image sequences; 3D reconstruction; computer vision; high order equation; image sequences; projective-invariant; second-order Lagrange multiplier; synthetic data; triangulation method; triangulation problem; Computer science; Cost function; Educational institutions; Image reconstruction; Image sequences; Intelligent networks; Intelligent systems; Lagrangian functions; Polynomials; Software; 3D reconstruction; computer vision; triangulation;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Networks and Intelligent Systems, 2009. ICINIS '09. Second International Conference on

Conference_Location

Tianjin

Print_ISBN

978-1-4244-5557-7

Electronic_ISBN

978-0-7695-3852-5

Type

conf

DOI

10.1109/ICINIS.2009.84

Filename

5365864