Gauge-based reliability analysis of 3D reconstruction from two uncalibrated perspective views

Author

Kanatani, Kenichi

Author_Institution

Dept. of Comput. Sci., Gunma Univ., Japan

Volume

1

fYear

2000

fDate

2000

Firstpage

76

Abstract

We evaluate the reliability of the 3D (Euclidean) shape reconstructed from two uncalibrated perspective views. Introducing a statistical model of image noise, we optimally compute the fundamental matrix and evaluate its uncertainty in quantitative terms. We then evaluate the covariance matrices of the reconstructed 3D points by propagating the image noise and the uncertainty in the fundamental matrix using a simple scheme. We show real-image experiments and discuss the effect of the “gauge” on the uncertainty description

Keywords

covariance matrices; image reconstruction; noise; optimisation; reliability; statistical analysis; stereo image processing; 3D reconstruction; 3D shape reconstruction; Euclidean shape reconstruction; covariance matrices; fundamental matrix; gauge-based reliability analysis; image noise; image noise propagation; statistical model; uncalibrated perspective views; uncertainty propagation; Cameras; Computer science; Covariance matrix; Error analysis; Image reconstruction; Noise shaping; Reliability theory; Shape; Three dimensional displays; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2000. Proceedings. 15th International Conference on

Conference_Location

Barcelona

ISSN

1051-4651

Print_ISBN

0-7695-0750-6

Type

conf

DOI

10.1109/ICPR.2000.905279

Filename

905279