Abstract
Multi-camera systems are widely applied in the three dimensional (3D) computer vision, especially when multiple cameras are distributed on both sides of the measured object. The calibration methods of multi-camera systems 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-camera systems based on transparent glass checkerboards and ray tracing is described, and is used to calibrate multiple cameras distributed on both sides of the glass checkerboard. Firstly, the intrinsic parameters of each camera are 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 the other side are influenced by the refraction of glass checkerboard, and the direct use of projection model will produce a calibration error. A multi-camera 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 the four-camera system are 0.00007 and 0.4543 pixels, respectively. The proposed method is flexible, highly accurate, and simple to carry out.
Highlights
Multi-camera systems (MCSs) have many advantages over single cameras because they can cover wider and more complete fields of view (FOVs), which makes MCSs increasingly prevalent in industrial vision measurements [1,2], visual navigation [3,4], and security monitoring [5], etc
In order to overcome the shortcomings of the foregoing methods, and guarantee high accuracy and convenience of multi-camera calibration, we propose a novel method of global calibration for and convenience of multi-camera calibration, we propose a novel method of global calibration for multiple cameras with overlapping FOVs
A typical MCS is installed on both sides of the measured object, which makes it difficult to calibrate the system using the existing camera calibration methods
Summary
Multi-camera systems (MCSs) have many advantages over single cameras because they can cover wider and more complete fields of view (FOVs), which makes MCSs increasingly prevalent in industrial vision measurements [1,2], visual navigation [3,4], and security monitoring [5], etc. Several patterns were proposed for multi-camera metric calibration, which can be to calculate stable and accurate calibration results, forms a partplanar of metric ratherand than self-calibration grouped into three main categories: 3D calibration targets, targets, one-dimensional approaches. Several patterns were proposed for multi-camera metric calibration, which can be grouped targets. The planar calibration pattern limits the distribution of multiple cameras, especially when target. The advantage is that all cameras are calibrated simultaneously, which avoids the accumulation of the accumulation of errors when multi-camera calibration is performed in steps or groups. This errors when multi-camera calibration is performed in steps or groups This camera calibration method camera calibration method has been widely used by many MCSs [10,17,18,19,20,21].
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