A Global Calibration Method for Widely Distributed Cameras Based on Vanishing Features

Wu, Xiaolong; Wu, Sentang; Zhang, Xing; Xiang, Jia

doi:10.3390/s16060838

Cited by 5 publications

(4 citation statements)

References 26 publications

(38 reference statements)

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“…A calibration target is a workpiece with high precision and can be used for feature extraction and precision verification in camera calibration [14,15,[19][20][21]23,[25][26][27][28]32,81]. Planar calibration target is the most widely used calibration target, whose plane consistency is good, and features are easy to extract.…”

Section: Methods Based On Large-scale Targetsmentioning

confidence: 99%

Global calibration of non-overlapping cameras: State of the art

Xia

Zhao

et al. 2018

Optik

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Section: Methods Based On Large-scale Targetsmentioning

confidence: 99%

Global calibration of non-overlapping cameras: State of the art

Xia

Zhao

et al. 2018

Optik

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“…The most commonly used camera calibration method is the vanishing point and the vanishing line method to calibrate. Reference [1]…”

Section: Introductionmentioning

confidence: 99%

Calibration Method Based on the Image of the Absolute Quadratic Curve

Liu

et al. 2019

IEEE Access

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In this paper, a new camera calibration method based on the image of the absolute quadratic curve (IAC) is proposed, and a new target is designed for this method, which is both convenient and flexible. It first extracts the characteristic points and the characteristic lines of the target and finds out the vanishing point and the vanishing line. The radial and tangential distortion coefficients are obtained by using the cross ratio invariance to correct the target image distortion. Then, the four internal parameters of the camera are obtained by IAC. The influence of the skew parameters is ignored. The rotation matrix is then calculated by the orthogonal characteristic of the coordinate system, and the translation vector is calculated by the center coordinates of the camera. In this way, the internal and external parameters of the camera can be obtained. The internal and external parameters are taken as initial values, and the optimal results are obtained by nonlinear optimization using the reprojection method. Finally, the relative position between different target images can be obtained by using the fundamental matrix, namely, the rotation angle. In the process of solving, the normalization method is used to improve the accuracy of data processing. Not requiring any prior information of the camera, the method has a wide range of applications. INDEX TERMS Camera calibration, image of the absolute quadratic curve (IAC), fundamental matrix, cross ratio invariance, vanishing point, vanishing line, distortion correction.

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“…In addition, the specially designed target is constructed of two mutually orthogonal groups of parallel lines with known lengths. Zhang et al [ 19 ] proposed a novel method based on spherical target images with certain size, which implements synchronous calibration of a multi-camera system. At present, the spherical target with extremely high quality is hard to manufacture.…”

Section: Introductionmentioning

confidence: 99%

Calibration of Binocular Vision Sensors Based on Unknown-Sized Elliptical Stripe Images

Liu

Yin

et al. 2017

Sensors

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Most of the existing calibration methods for binocular stereo vision sensor (BSVS) depend on a high-accuracy target with feature points that are difficult and costly to manufacture. In complex light conditions, optical filters are used for BSVS, but they affect imaging quality. Hence, the use of a high-accuracy target with certain-sized feature points for calibration is not feasible under such complex conditions. To solve these problems, a calibration method based on unknown-sized elliptical stripe images is proposed. With known intrinsic parameters, the proposed method adopts the elliptical stripes located on the parallel planes as a medium to calibrate BSVS online. In comparison with the common calibration methods, the proposed method avoids utilizing high-accuracy target with certain-sized feature points. Therefore, the proposed method is not only easy to implement but is a realistic method for the calibration of BSVS with optical filter. Changing the size of elliptical curves projected on the target solves the difficulty of applying the proposed method in different fields of view and distances. Simulative and physical experiments are conducted to validate the efficiency of the proposed method. When the field of view is approximately 400 mm × 300 mm, the proposed method can reach a calibration accuracy of 0.03 mm, which is comparable with that of Zhang’s method.

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A Global Calibration Method for Widely Distributed Cameras Based on Vanishing Features

Cited by 5 publications

References 26 publications

Global calibration of non-overlapping cameras: State of the art

Global calibration of non-overlapping cameras: State of the art

Calibration Method Based on the Image of the Absolute Quadratic Curve

Calibration of Binocular Vision Sensors Based on Unknown-Sized Elliptical Stripe Images

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