Conference paper
Euclidean reconstruction from an image triplet: a sensitivity analysis
Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170), Vol.1, pp.835-837
IEEE
14th International Conference on Pattern Recognition (Brisbane, Queensland, 16/08/1998–20/08/1998)
1998
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.
Details
- Title
- Euclidean reconstruction from an image triplet: a sensitivity analysis
- Authors/Creators
- D.Q. Huynh (Author/Creator) - Murdoch University
- Publication Details
- Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170), Vol.1, pp.835-837
- Conference
- 14th International Conference on Pattern Recognition (Brisbane, Queensland, 16/08/1998–20/08/1998)
- Publisher
- IEEE
- Identifiers
- 991005543803907891
- Copyright
- International Association for Pattern Recognition
- Murdoch Affiliation
- School of Information Technology
- Language
- English
- Resource Type
- Conference paper
- Note
- Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This paper appears in: Proceedings of the 14th International Conference on Pattern recognition, 1998, pp 835 - 837.
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