JOURNAL ARTICLE

Theoretical Uncertainty Evaluation of Stereo Reconstruction

Abstract

This paper deals with the problem of evaluating the uncertainties associated with linear camera model based stereo reconstruction using the law of propagation of uncertainty. The procedure of stereo reconstruction involves two consecutive stages: calibrating camera models and reconstructing a 3D point from its image projections. The output quantities of the first stage, the parameters of camera models, constitute a part of the input quantities of the second stage. The analytical expressions for uncertainty propagation during reconstructing a 3D point are proposed, and the results of an experiment with synthetic data are also presented. The experiment results show that there is at least one significant digit in the evaluated uncertainties associated with the reconstructed coordinates of a 3D point.

Keywords:
Artificial intelligence Computer vision Point (geometry) Computer science 3D reconstruction Iterative reconstruction Stereopsis Propagation of uncertainty Stereo camera Measurement uncertainty Algorithm Mathematics Geometry

Metrics

20
Cited By
1.77
FWCI (Field Weighted Citation Impact)
6
Refs
0.89
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Optical measurement and interference techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Robotics and Sensor-Based Localization
Physical Sciences →  Engineering →  Aerospace Engineering
© 2026 ScienceGate Book Chapters — All rights reserved.