Multi-Camera Network Calibration with a Non-Planar Target

Shen, Edward; Hornsey, Richard

doi:10.1109/jsen.2011.2123884

Cited by 25 publications

(27 citation statements)

References 19 publications

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“…One possibility is to use a known calibration object, such as a checkerboard pattern, that is simultaneously observed by all nodes [2], [3], [4]. Some authors have recently proposed to observe the object through planar mirror reflections in order to handle situations of little or no overlap in the FOVs [5], [6].…”

Section: Introductionmentioning

confidence: 99%

Automatic Camera Calibration Using Multiple Sets of Pairwise Correspondences

Vasconcelos¹,

Barreto²,

Boyer³

2018

IEEE Trans. Pattern Anal. Mach. Intell.

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Abstract-We propose a new method to add an uncalibrated node into a network of calibrated cameras using only pairwise point correspondences. While previous methods perform this task using triple correspondences, these are often difficult to establish when there is limited overlap between different views. In such challenging cases we must rely on pairwise correspondences and our solution becomes more advantageous. Our method includes an 11-point minimal solution for the intrinsic and extrinsic calibration of a camera from pairwise correspondences with other two calibrated cameras, and a new inlier selection framework that extends traditional RANSAC to sampling across multiple datasets. Our method is validated on different application scenarios where a lack of triple correspondences might occur: addition of a new node to a camera network; calibration and motion estimation of a moving camera inside a camera network; and addition of views with limited overlap to a Structure-from-Motion model.

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Section: Introductionmentioning

confidence: 99%

Automatic Camera Calibration Using Multiple Sets of Pairwise Correspondences

Vasconcelos¹,

Barreto²,

Boyer³

2018

IEEE Trans. Pattern Anal. Mach. Intell.

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“…A representative calibration scenario of multi-cameras begins by placing calibration target in the overlapping FOV of the cameras to provide a projection relationship between image and world points [10]. The standard calibration target is a planar pattern, such as checkerboard.…”

Section: Introductionmentioning

confidence: 99%

“…The advantage is that all cameras are calibrated simultaneously, which avoids the accumulation of errors when multi-cameras calibration is performed in steps or groups. Therefore, this camera calibration method has been widely used by many MCS [10,[17][18][19][20][21]. However, the disadvantages of 1D calibration target including [21]: 1) In the construction of the 1D pattern, it is not possible to guarantee the exact linearity of the points, hurting one of the main assumptions of the adopted model.…”

Section: Introductionmentioning

confidence: 99%

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

Feng

Xiang

Wang

et al. 2017

Preprint

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Multi-cameras system is widely applied in 3D computer vision especially when multiple 11 cameras are distributed on both sides of the measured object. The calibration methods of multi-12 cameras system are critical to the accuracy of vision measurement and the key is to find an 13 appropriate calibration target. In this paper, a high-precision camera calibration method for multi- 14cameras system based on transparent glass checkerboard and ray tracing is described, which is used 15 to calibrate multiple cameras distributed on both sides of the glass checkerboard. Firstly, the

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“…By formulating constraints between cameras and the mirrored calibration object, the extrinsic parameters can be deduced simply. For the purpose of overcoming the shortcomings of view angle, a calibration method using a non-planar target is presented in [6]. As the projection of a sphere is not related to its orientation, a target consisting of several spheres is used to finish the task of calibration.…”

Section: Introductionmentioning

confidence: 99%

Novel Calibration Method for the Multi-Camera Measurement System

Wang

2014

Journal of the Optical Society of Korea

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In a multi-camera measurement system, the determination of the external parameters is one of the vital tasks, referred to as the calibration of the system. In this paper, a new geometrical calibration method, which is based on the theory of the vanishing line, is proposed. Using a planar target with three equally spaced parallel lines, the normal vector of the target plane can be confirmed easily in every camera coordinate system of the measurement system. By moving the target into more than two different positions, the rotation matrix can be determined from related theory, i.e., the expression of the same vector in different coordinate systems. Moreover, the translation matrix can be derived from the known distance between the adjacent parallel lines. In this paper, the main factors effecting the calibration are analyzed. Simulations show that the proposed method achieves robustness and accuracy. Experimental results show that the calibration can reach 1.25 mm with the range about 0.5m. Furthermore, this calibration method also can be used for auto-calibration of the multi-camera measurement system as the feature of parallels exists widely.

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Multi-Camera Network Calibration with a Non-Planar Target

Cited by 25 publications

References 19 publications

Automatic Camera Calibration Using Multiple Sets of Pairwise Correspondences

Automatic Camera Calibration Using Multiple Sets of Pairwise Correspondences

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

Novel Calibration Method for the Multi-Camera Measurement System

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