Calibration of quad-camera measurement systems using a one-dimensional calibration object for three-dimensional point reconstruction

Li, Yunhui; Huo, Ju; Liu, Jia; Yang, Ming

doi:10.1117/1.oe.58.6.064107

Cited by 5 publications

(1 citation statement)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The conversion matrix T camB camA between the two camera coordinate systems and the conversion matrix T camA align between the camera A coordinate system and the alignment coordinate system can be obtained by prior calibration. By using the coordinates of the cooperation targets 1, 2 in the reference frame O − XY Z and their corresponding image plane coordinates, the rotation matrix R 1 and translation matrix t 1 from the reference frame to the alignment frame can be determined based on (5) and (6). From t 1 = (t x1 , t y1 , t z1 ) T , R 1 = R and t = −R 1 t 1 , the translation matrix t = (t x , t y , t z ) T from the upper alignment coordinate system to the bottom reference coordinate system can be obtained; subsequently, the horizontal alignment deviations t x and t y between the upper and lower parts can be determined.…”

Section: Model Of Position Measurementmentioning

confidence: 99%

Method for Horizontal Alignment Deviation Measurement Using Binocular Camera Without Common Target

Wang

Shen

et al. 2020

IEEE Access

View full text Add to dashboard Cite

In the application of using binocular camera to measure the horizontal alignment deviation, due to the limited field of view of the camera, it is difficult for each camera to obtain all the target points to determine the position of the parts. To this end, a binocular position measurement model, where each optical camera corresponds to one cooperative target point, is established to determine the horizontal alignment deviation between the upper and lower parts. To overcome the problem of insufficient information in calculating the horizontal alignment deviation, the measurement data of a biaxial inclinometer and laser rangefinder are added. The Monte Carlo method is used to determine the error level for any position and attitude in the measurement range based on past work experience. The high accuracy of the position measurement method (the overall error does not exceed 2 mm) for a binocular camera without a common target meets the actual application requirements. This conclusion is verified by the experimental results. INDEX TERMS Binocular position measurement, horizontal alignment deviation, no common target, biaxial inclinometer, laser ranging, Monte Carlo method

show abstract

Section: Model Of Position Measurementmentioning

confidence: 99%

Method for Horizontal Alignment Deviation Measurement Using Binocular Camera Without Common Target

Wang

Shen

et al. 2020

IEEE Access

View full text Add to dashboard Cite

show abstract

A 3D calibration method for binocular vision system

He,

Ji,

et al. 2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

Binocular vision system calibration is extremely important in three-dimensional (3D) measurement. During the calibration process, the establishment of an appropriate objective function has a direct impact on the calibration accuracy. For common two-dimensional (2D) calibration methods, differences in 2D calibration and 3D measurement coordinate systems result in loss of accuracy. Furthermore, for the newly proposed 3D calibration methods, the epipolar constraints in the 2D pixel coordinate system and the reconstruction errors in the 3D physical space need to be balanced by weights, resulting in uncertainties in the calibration results. To address these issues, we propose a novel calibration method that minimizes the distances between the control point and the left and right camera rays. The distances between the control points and the camera rays describe the 3D reconstruction errors, and the distances between the left camera and the right camera rays describe the geometry information between the two cameras to ensure that the epipolar constraints are satisfied. As a result, these two types of constraints/errors are measured under the same 3D coordinate system. Therefore, the epipolar constraints and the reconstruction errors are naturally balanced. We have conducted computer simulations and real experiments, and the results show that the proposed calibration method is effective in improving the accuracy compared with the state-of-the-art methods.

show abstract

Parallel optimization of tridimensional deformation measurement based on correlation function constraints of a multi-camera network

Gao¹,

Liang²,

Zhang³

et al. 2022

Appl. Opt.

View full text Add to dashboard Cite

This study primarily investigates the low accuracy and redundant time-consuming problem of speckle registration in the full-field deformation measurement of slender and biggish specimens. To solve these problems, a parallel optimization of the tridimensional deformation measurement method is proposed based on what we believe is a novel correlation function constraints of a multi-camera network. First, a neotype correlation function is built based on the joint constraint relationship among the multiple cameras, which is capable of accurately restricting the search for homologous points in image pairs to the epipolar line, instead of the entire image, while significantly narrowing the search space and accelerating the search. The multiple cameras are bundled as a whole, thus reducing the dimension of the Jacobian matrix and the normalized matrix to a certain extent. Subsequently, more speckle images can be calculated in one iteration. Furthermore, the decomposition of the derived correlation function and the scheme of the parallel algorithm are decomposed via the kernel function based on the GPU parallel mechanism of the compute unified device architecture source program, thus increasing the subpixel search speed of speckle matching and ensuring the calculation performance of the stereo deformation measurement method to reach a higher level. Lastly, the experimental results revealed that the proposed strategy could allow the calculation speed-up ratio of speckle sequence and stereo registration to reach 20.390 times and 17.873 times, respectively, while ensuring the out-of-plane displacement average measuring accuracy to be higher than 0.179 mm within the spatial range of [2 m, 2 m, 3 m]. As a result, the proposed approach has crucial applications in rapid and stable tridimensional deformation measurement.

show abstract

Calibration of quad-camera measurement systems using a one-dimensional calibration object for three-dimensional point reconstruction

Cited by 5 publications

References 21 publications

Method for Horizontal Alignment Deviation Measurement Using Binocular Camera Without Common Target

Method for Horizontal Alignment Deviation Measurement Using Binocular Camera Without Common Target

A 3D calibration method for binocular vision system

Parallel optimization of tridimensional deformation measurement based on correlation function constraints of a multi-camera network

Contact Info

Product

Resources

About