Global calibration method for non-overlapping cameras based on mobilephone screens in defocus scene

Author(s):  
Bing Zhang ◽  
Yang Gao
Author(s):  
Mingchi Feng ◽  
Xiang Jia ◽  
Jingshu Wang ◽  
Song Feng ◽  
Taixiong Zheng

Multi-cameras system is widely applied in 3D computer vision especially when multiple cameras are distributed on both sides of the measured object. The calibration methods of multi-cameras system are critical to the accuracy of vision measurement and the key is to find an appropriate calibration target. In this paper, a high-precision camera calibration method for multi-cameras system based on transparent glass checkerboard and ray tracing is described, which is used to calibrate multiple cameras distributed on both sides of the glass checkerboard. Firstly, the intrinsic parameters of each camera is obtained by Zhang’s calibration method. Then, multiple cameras capture several images from the front and back of the glass checkerboard with different orientations, and all images contain distinct grid corners. As the cameras on one side are not affected by the refraction of glass checkerboard, extrinsic parameters can be directly calculated. However, the cameras on another side are influenced by the refraction of glass checkerboard, and the direct use of projection model will produce calibration error. A multi-cameras calibration method using refractive projection model and ray tracing is developed to eliminate this error. Furthermore, both synthetic and real data are employed to validate the proposed approach. The experimental results of refractive calibration show that the error of the 3D reconstruction is smaller than 0.2 mm, the relative errors of both rotation and translation are less than 0.014%, and the mean and standard deviation of reprojection error of 4-cameras system are 0.00007 and 0.4543 pixel. The proposed method is flexible, high accurate, and simple to carry out.


1994 ◽  
Vol 2 (3) ◽  
pp. 163-175 ◽  
Author(s):  
G. Sinnaeve ◽  
P. Dardenne ◽  
R. Agneessens

This paper investigates the effect of spectral data pre-treatment by using scatter correction techniques, detrending and derivatives on the standard error of NIR predictive models. It is shown that no particular spectral pre-treatment or no single derivative works best for the three constituents (protein, cellulose, organic matter digestibility) of the three forage databases which we investigated (grass-hay, tropical forages, maize whole plants). The best analytical results are obtained with SNVD, MSC or WMSC treatments. The best results are obtained with a first or second derivative with a segment and a gap of five data points. Local Regression was investigated for the prediction of forage quality. The standard errors of prediction were compared with those obtained with the best global calibration. Trial and error is the only way to fix the number of samples in the subset and the number of terms to retain in the model. Compared to the results for the traditional universal calibration method, the gain in SEP for protein, cellulose and digestibility in grass-hay, tropical forages or maize ranges between 5 and 11%.


2016 ◽  
Author(s):  
Dongzhao Huang ◽  
Qiancheng Zhao ◽  
Yun Ou ◽  
Tianlong Yang

2016 ◽  
Vol 16 (4) ◽  
pp. 190-196 ◽  
Author(s):  
Guan Xu ◽  
Xinyuan Zhang ◽  
Xiaotao Li ◽  
Jian Su ◽  
Zhaobing Hao

Abstract We present a reliable calibration method using the constraint of 2D projective lines and 3D world points to elaborate the accuracy of the camera calibration. Based on the relationship between the 3D points and the projective plane, the constraint equations of the transformation matrix are generated from the 3D points and 2D projective lines. The transformation matrix is solved by the singular value decomposition. The proposed method is compared with the point-based calibration to verify the measurement validity. The mean values of the root-mean-square errors using the proposed method are 7.69×10−4, 6.98×10−4, 2.29×10−4, and 1.09×10−3 while the ones of the original method are 8.10×10−4, 1.29×10−2, 2.58×10−2, and 8.12×10−3. Moreover, the average logarithmic errors of the calibration method are evaluated and compared with the former method in different Gaussian noises and projective lines. The variances of the average errors using the proposed method are 1.70×10−5, 1.39×10−4, 1.13×10−4, and 4.06×10−4, which indicates the stability and accuracy of the method.


2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Yang Zhang ◽  
Wei Liu ◽  
Zhiguang Lan ◽  
Zhiyuan Zhang ◽  
Fan Ye ◽  
...  

Considering the limited measurement range of a machine vision method for the three-dimensional (3D) surface measurement of large-scale components, a noncontact and flexible global measurement method combining a multiple field of view (FOV) is proposed in this paper. The measurement system consists of two theodolites and a binocular vision system with a transfer mark. The process of multiple FOV combinations is described, and a new global calibration method is proposed to solve the coordinate system unification issue of different instruments in the measurement system. In addition, a high-precision image acquisition method, which is based on laser stripe scanning and centre line extraction, is discussed to guarantee the measurement efficiency. With the measured 3D data, surface reconstruction of large-scale components is accomplished by data integration. Experiments are also conducted to verify the precision and effectiveness of the global measurement method.


2013 ◽  
Vol 718-720 ◽  
pp. 868-874 ◽  
Author(s):  
Wen Sun

To address the problems of low efficiency, high cost and low automatic level existing in traditional laser tracking measurement systems, a laser tracking-vision guiding measurement system for large-scale parts assembly is introduced in this paper. The system is composed of mono-camera and a laser tracker, can fulfill real-time tracking and automatic measurement throughout the whole assembly process. A global calibration method based on public planes and a method for finding the 3D positions of the target reflectors based on monocular vision measuring are expounded. Mathematical model is established, measurement system is built, and the experiment is accomplished. The experiment result indicates that the proposed system features relative high degree of automation and high measuring speed, has future in practical application.


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