Dioptric Fisheye Panoramic Camera Calibration Based on Unifying Spherical Projection Model

2012 ◽  
Vol 268-270 ◽  
pp. 1553-1557
Author(s):  
Ke Wang ◽  
Liang Liang Wang ◽  
Li Jun Zhao ◽  
Rui Feng Li
Keyword(s):  
Hough Transform ◽  
Optimization Technique ◽  
Calibration Method ◽  
Corner Detection ◽  
Projection Model ◽  
Fisheye Camera ◽  
Detection Window ◽  
Edge Based ◽  
Spherical Projection ◽  
Fish Eye

In this paper, a calibration method is proposed for fish-eye panoramic camera. We adopt the unifying spherical projection model to represent the optical nature of fisheye camera. Traditional corner detection works unreliably in highly distorted image. Therefore, edge-based corner detection is proposed based on Hough transform. The line segments within corner detection window and their intersection corner points are extracted accurately and reliably due to the robustness of Hough transform. We use the nonlinear optimization technique to estimate the camera parameters. Experimental results demonstrate the performance of our method.

scholarly journals Global Calibration of Multi-Cameras Based on Refractive Projection and Ray Tracing

2017 ◽  
Author(s):  
Mingchi Feng ◽  
Xiang Jia ◽  
Jingshu Wang ◽  
Song Feng ◽  
Taixiong Zheng
Keyword(s):  
Ray Tracing ◽  
Real Data ◽  
Calibration Method ◽  
Calibration Error ◽  
Multiple Cameras ◽  
Projection Model ◽  
Vision Measurement ◽  
3D Computer Vision ◽  
Global Calibration ◽  
Calibration Methods

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.

Panoramic Display System Geometric Calibration Method Based on Fisheye Camera

2017 ◽  
Vol 54 (2) ◽  
pp. 021501
Author(s):  
肖朝 Xiao Chao ◽  
陈锋 Chen Feng ◽  
钟敏 Zhong Min ◽  
金川 Jin Chuan
Keyword(s):  
Calibration Method ◽  
Display System ◽  
Geometric Calibration ◽  
Fisheye Camera

Checkerboard Corner Detection Based on Hough Transform and Circular Template

2020 ◽  
Vol 57 (18) ◽  
pp. 181510
Author(s):  
杨炜松 Yang Weisong ◽  
郭帅平 Guo Shuaiping ◽  
李学军 Li Xuejun ◽  
李鸿光 Li Hongguang
Keyword(s):  
Hough Transform ◽  
Corner Detection ◽  
Circular Template

Geometric parameter identification of a dual-arm robot by using closed-chain constraint and optimization technique

2017 ◽  
Vol 232 (7) ◽  
pp. 1294-1302 ◽  
Author(s):  
Wu-Te Yang ◽  
Kuan-Lin Li ◽  
Kuei-Yuan Chan ◽  
Pei-Chun Lin
Keyword(s):  
Optimization Technique ◽  
Constraint Equation ◽  
Calibration Method ◽  
Kinematic Parameter ◽  
Motion Generation ◽  
Positioning Accuracy ◽  
Closed Chain ◽  
Controller Performance ◽  
Dual Arm Robot ◽  
Dual Arm

The positioning accuracy of the empirical robot manipulators is determined by various factors, such as kinematic accuracy, structure rigidity, and controller performance. Here, we report on the development of a new and straightforward technique to calibrate the kinematic parameters of a dual-arm robot under uncertainty. In comparison with other techniques, which generally rely on using other instruments to calibrate the manipulators, the proposed method utilizes the intrinsic characteristics of the dual-arm robot for calibration. In particular, when the two arms grasp each other, a formed closed chain can be operated as the constraint equation for the kinematic parameter optimization of the two arms. In the optimization process, the dual-arm robot has to pose in various configurations to yield better performance, and thus a motion generation strategy of the dual-arm robot is proposed, where one arm serves as the master to track the designated trajectory and the other arm serves as the slave to track the motion of the master arm by using a compliance control strategy. The proposed calibration method was experimentally validated, and the results confirm that the positioning accuracy of both arms can be improved.

An improved vision calibration method for coaxial alignment microassembly

2014 ◽  
Vol 34 (3) ◽  
pp. 237-243 ◽  
Author(s):  
Xin Ye ◽  
Jun Gao ◽  
Zhijing Zhang ◽  
Chao Shao ◽  
Guangyuan Shao
Keyword(s):  
Degrees Of Freedom ◽  
Microelectromechanical Systems ◽  
Vision System ◽  
Image Plane ◽  
Calibration Method ◽  
Corner Detection ◽  
Objective Lens ◽  
Content Type ◽  
Assembly Accuracy ◽  
Methodological Guidelines

Purpose – The purpose of this paper is to propose a sub-pixel calibration method for a microassembly system with coaxial alignment function (MSCA) because traditional sub-pixel calibration approaches cannot be used in this system. Design/methodology/approach – The in-house microassembly system comprises a six degrees of freedom (6-DOF) large motion serial robot with microgrippers, a hexapod 6-DOF precision alignment worktable and a vision system whose optical axis of the microscope is parallel with the horizontal plane. A prism with special coating is fixed in front of the objective lens; thus, two parts’ Figures, namely the images of target and base part, can be acquired simultaneously. The relative discrepancy between the two parts can be calculated from image plane coordinate instead of calculating space transformation matrix. Therefore, the traditional calibration method cannot be applied in this microassembly system. An improved calibration method including the check corner detection solves the distortion coefficient conversely. This new way can detect the corner at sub-pixel accuracy. The experiment proves that the assembly accuracy of the coaxial microassembly system which has been calibrated by the new method can reach micrometer level. Findings – The calibration results indicate that solving the distortion conversely could improve the assembly accuracy of MSCA. Originality/value – The paper provides certain calibration methodological guidelines for devices with 2 dimensions or 2.5 dimensions, such as microelectromechanical systems devices, using MSCA.

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