Euclidean reconstruction from an image triplet: a sensitivity analysis

Author

Huynh, D.Q.

Author_Institution

Dept. of Inf. Technol., Murdoch Univ., WA, Australia

Volume

1

fYear

1998

fDate

16-20 Aug 1998

Firstpage

835

Abstract

This paper studies the sensitivity in Euclidean reconstruction from an image triplet taken by an uncalibrated camera mounted on a robot arm. The idea of such a reconstruction is closely related to that proposed by Zisserman et al. (1995). In this paper, we focus on an intermediate step of the reconstruction procedure which requires estimating the screw axis that corresponds to the defective eigenvector of a 4×4 matrix. Hundreds of the conducted synthetic tests show that the algorithm is very sensitive to image noise and perturbations on camera motions and that if the matrix is perturbed by Gaussian noise then the reliability of the computed screw axis can be estimated

Keywords

Gaussian noise; eigenvalues and eigenfunctions; image reconstruction; matrix algebra; object recognition; robot vision; sensitivity analysis; stereo image processing; 3D map; Euclidean reconstruction; Gaussian noise; camera motions; defective eigenvector; image triplet; object recognition; perturbations; robot vision; screw axis; sensitivity analysis; Cameras; Eigenvalues and eigenfunctions; Fasteners; Gaussian noise; Image reconstruction; Information technology; Robot sensing systems; Robot vision systems; Sensitivity analysis; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on

Conference_Location

Brisbane, Qld.

ISSN

1051-4651

Print_ISBN

0-8186-8512-3

Type

conf

DOI

10.1109/ICPR.1998.711279

Filename

711279