New multiple-camera calibration method for a large number of cameras

2005 ◽  
Author(s):  
Yuuya Kojima ◽  
Toshiaki Fujii ◽  
Masayuki Tanimoto
Keyword(s):  
Camera Calibration ◽  
Calibration Method ◽  
Multiple Camera

Camera Calibration Method Based on Circle Plane Board

2013 ◽  
Vol 475-476 ◽  
pp. 184-187
Author(s):  
Wen Guo Li ◽  
Shao Jun Duan
Keyword(s):  
Camera Calibration ◽  
Calibration Method ◽  
Lens Distortion ◽  
Edge Extraction ◽  
Circle Plane ◽  
Circle Centre ◽  
Extraction Algorithm ◽  
Calibration Algorithm ◽  
Characteristic Points ◽  
Distortion Parameters

We present a camera calibration method based on circle plane board. The centres of circles on plane are regarded as the characteristic points, which are used to implement camera calibration. The proposed calibration is more accurate than many previous calibration algorithm because of the merit of the coordinate of circle centre being obtained from thousand of of edge pionts of ellipse, which is very reliable to image noise caused by edge extraction algorithm. Experiments shows the proposed algorithm can obtain high precise inner parameters, and lens distortion parameters.

CCD Camera Calibration Technology Based on the Translation of Coordinate Measuring Machine

2014 ◽  
Vol 568-570 ◽  
pp. 320-325 ◽  
Author(s):  
Feng Shan Huang ◽  
Li Chen
Keyword(s):  
Coordinate System ◽  
Camera Calibration ◽  
Characteristic Point ◽  
Coordinate Measuring Machine ◽  
Ccd Camera ◽  
Mathematic Model ◽  
Calibration Method ◽  
Calibration Characteristic ◽  
Standard Sphere ◽  
Measuring Machine

A new CCD camera calibration method based on the translation of Coordinate Measuring Machine (CMM) is proposed. The CMM brings the CCD camera to produce the relative translation with respect to the center of the white ceramic standard sphere along the X, Y, Z axis, and the coordinates of the different positions of the calibration characteristic point in the probe coordinate system can be generated. Meanwhile, the camera captures the image of the white ceramic standard sphere at every position, and the coordinates of the calibration characteristic point in the computer frame coordinate system can be registered. The calibration mathematic model was established, and the calibration steps were given and the calibration system was set up. The comparing calibration result shows that precision of this method is equivalent to that of the special calibration method, and the difference between the calibrating data of these two methods is within ±1μm.

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.

Camera Calibration Method with Multi-condition Constraints Based on Laser Points

2021 ◽  
Vol 50 (4) ◽  
pp. 172-181
Author(s):  
李彩林 Cailin LI ◽  
苏本娅 Benya SU ◽  
郭宝云 Baoyun GUO ◽  
王志勇 Zhiyong WANG ◽  
朱夫宏 Fuhong ZHU
Keyword(s):  
Camera Calibration ◽  
Calibration Method

Industrial part localization and grasping using a robotic arm guided by 2D monocular vision

2018 ◽  
Vol 45 (6) ◽  
pp. 794-804 ◽  
Author(s):  
Zhaohui Zheng ◽  
Yong Ma ◽  
Hong Zheng ◽  
Yu Gu ◽  
Mingyu Lin
Keyword(s):  
Camera Calibration ◽  
High Precision ◽  
Calibration Method ◽  
Monocular Vision ◽  
Robotic Arm ◽  
Robot Arm ◽  
Content Type ◽  
Calibration Algorithm ◽  
Target Locating ◽  
Practical Implications

Purpose The welding areas of the workpiece must be consistent with high precision to ensure the welding success during the welding of automobile parts. The purpose of this paper is to design an automatic high-precision locating and grasping system for robotic arm guided by 2D monocular vision to meet the requirements of automatic operation and high-precision welding. Design/methodology/approach A nonlinear multi-parallel surface calibration method based on adaptive k-segment master curve algorithm is proposed, which improves the efficiency of the traditional single camera calibration algorithm and accuracy of calibration. At the same time, the multi-dimension feature of target based on k-mean clustering constraint is proposed to improve the robustness and precision of registration. Findings A method of automatic locating and grasping based on 2D monocular vision is provided for robot arm, which includes camera calibration method and target locating method. Practical implications The system has been integrated into the welding robot of an automobile company in China. Originality/value A method of automatic locating and grasping based on 2D monocular vision is proposed, which makes the robot arm have automatic grasping function, and improves the efficiency and precision of automatic grasp of robot arm.

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