Camera Calibration of Binocular Vision Based on Virtual 1D Target

2012 ◽  
Vol 605-607 ◽  
pp. 859-863
Author(s):  
Yu Bo Guo ◽  
Gang Chen ◽  
Dong Ye ◽  
Feng Yuan
Keyword(s):  
Binocular Vision ◽  
Constraint Equation ◽  
Calibration Method ◽  
Epipolar Constraint ◽  
Field Calibration ◽  
Extrinsic Parameter ◽  
Extrinsic Parameters ◽  
Virtual Target ◽  
Flexible Application ◽  
Easy Operation

A field calibration method based on virtual 1D target is proposed for the extrinsic parameters of binocular vision. A target is placed on high precision 1D lifting platform to create virtual 1D target through motions of lifting platform. Two cameras are used to obtain virtual target images of different positions and preliminarily achieve extrinsic parameter calibration of binocular vision based on epipolar constraint equation. Finally, the length of virtual 1-D target is used to optimize the extrinsic parameters. This method is featured with easy operation, flexible application and field calibration. The experimental results verify the feasibility of this calibration method and show it can yield high field calibration precision.

Computer Hard Disk Planeness Vision Measurement System Calibration Based on Light Plane Constraint

2013 ◽  
Vol 475-476 ◽  
pp. 63-67
Author(s):  
Rui Yin Tang ◽  
Zhou Mo Zeng ◽  
Peng Fei Li
Keyword(s):  
Nonlinear Model ◽  
Constraint Equation ◽  
Hard Disk ◽  
Calibration Method ◽  
Calibration Target ◽  
System Calibration ◽  
Vision Measurement ◽  
Light Plane ◽  
Fitting Method ◽  
Extrinsic Parameters

This paper proposed a calibration method of sheet-of-light vision measurement sensor based on light plane constraint. Through capturing 12 images of different direction from homemade circular calibration target, the center of the circle and the light stripe is extracted based on Halcon platform of Germany. The experimental results obtained the intrinsic parameters, extrinsic parameters and radial distortion coefficient of the nonlinear model. At the same time the light plane constraint equation is got based on PCA plane fitting method. The results show that the calibration method is simple and reliable, and the method does not need any auxiliary adjustment. The work laid the better foundation for hard disk planeness vision measurement.

scholarly journals Accurate binocular stereo underwater measurement method

2019 ◽  
Vol 16 (5) ◽  
pp. 172988141986446
Author(s):  
Xiaojun Wu ◽  
XingCan Tang
Keyword(s):  
Measurement Accuracy ◽  
Calibration Method ◽  
Correction Method ◽  
Image Correction ◽  
Underwater Imaging ◽  
Epipolar Constraint ◽  
Imaging Model ◽  
Internal Parameters ◽  
Extrinsic Parameters ◽  
Binocular Stereo

Light changes its direction of propagation before entering a camera enclosed in a waterproof housing owing to refraction, which means that perspective imaging models in the air cannot be directly used underwater. In this article, we propose an accurate binocular stereo measurement system in an underwater environment. First, based on the physical underwater imaging model without approximation and Tsai’s calibration method, the proposed system is calibrated to acquire the extrinsic parameters, as the internal parameters can be pre-calibrated in air. Then, based on the calibrated camera parameters, an image correction method is proposed to convert the underwater images to air images. Thus, the epipolar constraint can be used to search the matching point directly. The experimental results show that the proposed method in this article can effectively eliminate the effect of refraction in the binocular vision and the measurement accuracy can be compared with the measurement result in air.

scholarly journals Extrinsic Parameter Calibration Method for a Visual/Inertial Integrated System with a Predefined Mechanical Interface

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3086
Author(s):  
Ouyang ◽  
Shi ◽  
You ◽  
Zhao
Keyword(s):  
Euler Angle ◽  
Calibration Method ◽  
Integrated System ◽  
Corner Detection ◽  
Position Vector ◽  
Parameter Calibration ◽  
Body Frame ◽  
Extrinsic Parameter ◽  
Extrinsic Parameters ◽  
Mechanical Interface

For a visual/inertial integrated system, the calibration of extrinsic parameters plays a crucial role in ensuring accurate navigation and measurement. In this work, a novel extrinsic parameter calibration method is developed based on the geometrical constraints in the object space and is implemented by manual swing. The camera and IMU frames are aligned to the system body frame, which is predefined by the mechanical interface. With a swinging motion, the fixed checkerboard provides constraints for calibrating the extrinsic parameters of the camera, whereas angular velocity and acceleration provides constraints for calibrating the extrinsic parameters of the IMU. We exploit the complementary nature of both the camera and IMU, of which the latter assists in the checkerboard corner detection and correction while the former suppresses the effects of IMU drift. The results of the calibration experiment reveal that the extrinsic parameter accuracy reaches 0.04° for each Euler angle and 0.15 mm for each position vector component (1σ).

scholarly journals Phase-Based Calibration Method for a Binocular Vision Sensor

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 44354-44362
Author(s):  
Mingwei Shao ◽  
Pan Wang ◽  
Yanjun Wang
Keyword(s):  
Binocular Vision ◽  
Calibration Method ◽  
Vision Sensor

scholarly journals Extrinsic Parameters Calibration Method of Cameras with Non-Overlapping Fields of View in Airborne Remote Sensing

2018 ◽  
Vol 10 (8) ◽  
pp. 1298 ◽  
Author(s):  
Lei Yin ◽  
Xiangjun Wang ◽  
Yubo Ni ◽  
Kai Zhou ◽  
Jilong Zhang
Keyword(s):  
Remote Sensing ◽  
Camera Calibration ◽  
Calibration Method ◽  
Optimization Method ◽  
Airborne Remote Sensing ◽  
Camera System ◽  
Translation Error ◽  
Camera Systems ◽  
Calibration Methods ◽  
Extrinsic Parameters

Multi-camera systems are widely used in the fields of airborne remote sensing and unmanned aerial vehicle imaging. The measurement precision of these systems depends on the accuracy of the extrinsic parameters. Therefore, it is important to accurately calibrate the extrinsic parameters between the onboard cameras. Unlike conventional multi-camera calibration methods with a common field of view (FOV), multi-camera calibration without overlapping FOVs has certain difficulties. In this paper, we propose a calibration method for a multi-camera system without common FOVs, which is used on aero photogrammetry. First, the extrinsic parameters of any two cameras in a multi-camera system is calibrated, and the extrinsic matrix is optimized by the re-projection error. Then, the extrinsic parameters of each camera are unified to the system reference coordinate system by using the global optimization method. A simulation experiment and a physical verification experiment are designed for the theoretical arithmetic. The experimental results show that this method is operable. The rotation error angle of the camera’s extrinsic parameters is less than 0.001rad and the translation error is less than 0.08 mm.

scholarly journals Constrained Multiple Planar Reconstruction for Automatic Camera Calibration of Intelligent Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4643
Author(s):  
Sang Jun Lee ◽  
Jeawoo Lee ◽  
Wonju Lee ◽  
Cheolhun Jang
Keyword(s):  
Camera Calibration ◽  
Calibration Method ◽  
Image Features ◽  
Intelligent Vehicles ◽  
Point Problem ◽  
Reconstruction Method ◽  
Calibration Methods ◽  
The World ◽  
Extrinsic Parameters ◽  
Automatic Camera Calibration

In intelligent vehicles, extrinsic camera calibration is preferable to be conducted on a regular basis to deal with unpredictable mechanical changes or variations on weight load distribution. Specifically, high-precision extrinsic parameters between the camera coordinate and the world coordinate are essential to implement high-level functions in intelligent vehicles such as distance estimation and lane departure warning. However, conventional calibration methods, which solve a Perspective-n-Point problem, require laborious work to measure the positions of 3D points in the world coordinate. To reduce this inconvenience, this paper proposes an automatic camera calibration method based on 3D reconstruction. The main contribution of this paper is a novel reconstruction method to recover 3D points on planes perpendicular to the ground. The proposed method jointly optimizes reprojection errors of image features projected from multiple planar surfaces, and finally, it significantly reduces errors in camera extrinsic parameters. Experiments were conducted in synthetic simulation and real calibration environments to demonstrate the effectiveness of the proposed method.

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