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.

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.

A Camera Calibration Method Based on Plane Grid Points

2011 ◽  
Vol 230-232 ◽  
pp. 723-727 ◽  
Author(s):  
Bao Feng Zhang ◽  
Xiu Zhen Tian ◽  
Xiao Ling Zhang
Keyword(s):  
Camera Calibration ◽  
Model Calibration ◽  
Calibration Method ◽  
Translation Vector ◽  
Plane Model ◽  
Extrinsic Parameters ◽  
Computer Vision Systems ◽  
Grid Points ◽  
Intrinsic And Extrinsic Parameters ◽  
Plane Grid

In order to simplify previous camera calibration method, this paper put forward an easy camera calibration method based on plane grid points on the foundation of Heikkila plane model calibration method. Intrinsic and extrinsic parameters of the camera are calibrated with MATLAB, then the rotation matrix and the translation vector are calculated. The experiment results show this method is not only simple in practice, but also can meet the needs of computer vision systems.

A New Binocular Camera Calibration Method Based on an Improved Genetic Algorithm

2011 ◽  
Vol 411 ◽  
pp. 602-608 ◽  
Author(s):  
Xiang Kui Jiang
Keyword(s):  
Genetic Algorithm ◽  
Camera Calibration ◽  
Calibration Method ◽  
Improved Genetic Algorithm ◽  
Linear Calibration ◽  
Calibration Methods ◽  
Calibration Accuracy ◽  
Encoding Method ◽  
The One ◽  
Crossover And Mutation

In this paper,an improved genetic algorithm was proposed,which is applicable to binocular camera calibration. On the one hand, conventional encoding method is improved so that variable search interval can be adjusted adaptively. On the other hand, crossover and mutation probability is varied by using superiority inheritance principle to avoid premature question. Experimental results show that the proposed method has a higher calibration accuracy and better robustness, compared to those of non-linear calibration methods. The proposed method is able to improve the performance of global optimization effectively.

An automatic camera calibration method based on checkerboard

2017 ◽  
Vol 34 (3-4) ◽  
pp. 209-226
Author(s):  
QILIN BI ◽  
ZHIJUN LIU ◽  
MIAOHUI WANG ◽  
MINLING LAI ◽  
LEMING XIAO ◽  
...  
Keyword(s):  
Camera Calibration ◽  
Calibration Method ◽  
Automatic Camera Calibration

Investigation of Factors Influencing Calibration Accuracy of Camera

2013 ◽  
Vol 712-715 ◽  
pp. 2331-2335
Author(s):  
Jian Hua Wang ◽  
Yu Ping Wu ◽  
Zhao Yang
Keyword(s):  
Camera Calibration ◽  
Control Point ◽  
Calibration Method ◽  
Manufacturing Error ◽  
Manufacturing Tolerance ◽  
Factors Influencing ◽  
Calibration Methods ◽  
Machine Vision Application ◽  
Calibration Accuracy ◽  
Vision Application

Camera calibration is the basis of vision-based 3D measurement. While many calibration methods have been proposed, the problem encountered in the practice of camera calibration is how to get accurate calibration parameters, which is seldom involved in references. This paper is focused on investigation of main factors influencing calibration accuracy, including manufacturing error of calibration rig, extracting error of control point and their combination. Based on the popular calibration method, simulation experiments are conducted at different error level, and the results show that the extracting error of control point has greater effect on calibration accuracy than manufacturing error of calibration rig. The manufacturing tolerance of calibration rig and extracting tolerance of control point is suggested to satisfy usual machine vision application.

A Novel Camera Calibration Method Based on Simulated Annealing Genetic Algorithm

2015 ◽  
Vol 719-720 ◽  
pp. 1184-1190
Author(s):  
Shuang Ran ◽  
Long Ye ◽  
Jing Ling Wang ◽  
Qin Zhang
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Camera Calibration ◽  
Simulated Annealing Algorithm ◽  
Image Plane ◽  
Calibration Method ◽  
Simulated Annealing Genetic Algorithm ◽  
Extrinsic Parameters ◽  
Annealing Algorithm ◽  
Intrinsic And Extrinsic Parameters

The optimization of the camera’s intrinsic and extrinsic parameters is a key step after obtaining the initialized parameters’ state by considering the homography between the board space plane and the image plane in Zhengyou Zhang method. In this paper, we proposed a camera calibration optimization algorithm by adopting genetic algorithm and the simulated annealing algorithm. The experiment results demonstrate that our algorithm can improve the precision of the camera calibration to a certain extent.

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