Open AccessPrecise calibration of binocular vision system used for vision measurement
Author(s) -
Yi Cui,
Fuqiang Zhou,
Yexin Wang,
Liu Liu,
Gaohong He
Publication year - 2014
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.22.009134
Subject(s) - epipolar geometry , computer vision , artificial intelligence , computer science , binocular vision , reprojection error , calibration , machine vision , camera resectioning , metric (unit) , pixel , triangulation , fundamental matrix (linear differential equation) , image plane , coordinate system , observational error , mathematics , image (mathematics) , mathematical analysis , statistics , operations management , geometry , economics
Binocular vision calibration is of great importance in 3D machine vision measurement. With respect to binocular vision calibration, the nonlinear optimization technique is a crucial step to improve the accuracy. The existing optimization methods mostly aim at minimizing the sum of reprojection errors for two cameras based on respective 2D image pixels coordinate. However, the subsequent measurement process is conducted in 3D coordinate system which is not consistent with the optimization coordinate system. Moreover, the error criterion with respect to optimization and measurement is different. The equal pixel distance error in 2D image plane leads to diverse 3D metric distance error at different position before the camera. To address these issues, we propose a precise calibration method for binocular vision system which is devoted to minimizing the metric distance error between the reconstructed point through optimal triangulation and the ground truth in 3D measurement coordinate system. In addition, the inherent epipolar constraint and constant distance constraint are combined to enhance the optimization process. To evaluate the performance of the proposed method, both simulative and real experiments have been carried out and the results show that the proposed method is reliable and efficient to improve measurement accuracy compared with conventional method.