• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.250-255
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• 2003

The position of a 3-dimensional(3D) point can be measured by using calibrated stereo camera. To obtain more accurate measurement ,more accurate camera calibration is required. There are many existing methods to calibrate camera. The simple linear methods are usually not accurate due to nonlinear lens distortion. The nonlinear methods are accurate more than linear method, but it increase computational cost and good initial guess is needed. The multi step methods need to know some camera parameters of used camera. Recent years, these explicit model based camera calibration work with the development of more precise camera models involving correction of lens distortion. But these explicit model based camera calibration have disadvantages. So implicit camera calibration methods have been derived. One of the popular implicit camera calibration method is to use neural network. In this paper, we propose implicit stereo camera calibration method for 3D reconstruction using support vector machine. SVM can learn the relationship between 3D coordinate and image coordinate, and it shows the robust property with the presence of noise and lens distortion, results of simulation are shown in section 4.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.602-608
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• 2015

This paper proposes an algorithm for precise detection of corner points on a coplanar checkerboard in order to perform stereo camera calibration using a single frame. Considering the conditions of automobile production lines where a stereo camera is attached to the windshield of a vehicle, this research focuses on a coplanar calibration methodology. To obtain the accurate values of the stereo camera parameters using the calibration methodology, precise localization of a large number of feature points on a calibration target image should be ensured. To realize this demand, the idea with respect to a checkerboard pattern design and the use of a Homography matrix are provided. The calibration result obtained by the proposed method is also verified by comparing the depth information from stereo matching and a laser scanner.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.10-17
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• 2010

This paper presents a calibration method of an omnidirectional stereo camera which may be essentially performed for distance measurement to a certain point. In the calibration of the omnidirectional stereo camera, the independent calibrations of two cameras or the calibration of a stereo camera having the small baseline is feasible applying many methods studied in the past. However, the baseline should be large enough for long distance measurement by the omnidirectional stereo camera, since it is not easy to calibrate two cameras with a large baseline at the same time. It is because a test pattern for the calibration, which is simultaneously captured by two omnidirectional cameras, appears too small in at least one of the omnidirectional cameras. It causes inaccurate calibration. In this paper, therefore, we propose a calibration method of the omnidirectional stereo camera with a large baseline and empirically verify its feasibility.

• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.171-182
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• 2015

We propose a camera system to acquire indoor stereo omni-directional images and its calibration method. These images can be utilized for indoor precise mapping and sophisticated imagebased services. The proposed system is configured with a rotating stereo line camera system, providing stereo omni-directional images appropriate to stable stereoscopy and precise derivation of object point coordinates. Based on the projection model, we derive a mathematical model for the system calibration. After performing the system calibration, we can estimate object points with an accuracy of less than ${\pm}16cm$ in indoor space. The proposed system and calibration method will be applied to indoor precise 3D modeling.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.3
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• pp.224-229
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• 2007

This paper presents a camera calibration method using several images for three dimensional measurement applications such as stereo systems, mobile robots, and visual inspection systems in factories. Conventional calibration methods that use single image suffer from errors related to reference point extraction in image, lens distortion, and numerical analysis of nonlinear optimization. The camera parameter values obtained from images of same camera is not same even though we use same calibration method. The camera parameters that are obtained from several images of different view for a calibration target is usaully not same with large error values and we can not assume a special probabilistic distribution when we estimate the parameter values. In this paper, the median value of camera parameters from several images is used to improve estimation of the camera values in an iterative step with nonlinear optimization. The proposed method is proved by experiments using real images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.3
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• pp.123-132
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• 2021

To determine 3D(three-dimensional) positions using a stereo-camera in close-range photogrammetry, camera calibration to determine not only the interior orientation parameters of each camera but also the relative orientation parameters between the cameras must be preceded. As time passes after performing camera calibration, in the case of non-metric cameras, the interior and relative orientation parameters may change due to internal instability or external factors. In this study, to evaluate the stability of the stereo-camera, not only the stability of two single cameras and a stereo-camera were analyzed, but also the three-dimensional position accuracy was evaluated using checkpoints. As a result of evaluating the stability of two single cameras through three camera calibration experiments over four months, the root mean square error was ±0.001mm, and the root mean square error of the stereo-camera was ±0.012mm ~ ±0.025mm, respectively. In addition, as the results of distance accuracy using the checkpoint were ±1mm, the interior and relative orientation parameters of the stereo-camera were considered stable over that period.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.4
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• pp.295-303
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• 2018

The stereo camera system has a fixed baseline and therefore has a constant scale. However, it is difficult to measure the actual three-dimensional coordinate since the scale is not fixed when relative orientation parameters are determined through the key-point matching in the stereo image each time. Therefore, the purpose of this study was to perform the stereo camera calibration that simultaneously determines the internal characteristics of the left and right cameras and the camera relationship between them using the modified collinearity equation and compared it with the two independent single cameras calibration. In the experiment using the images taken at close range, the RMSE (Root Mean Square Error) of ${\pm}0.014m$ was occurred when the three dimensional distances were compared in the single calibration results. On the other hand, the accuracy of the three-dimensional distance of the stereo camera calibration was better because the stereo camera results were almost no error compared to the results from two single cameras. In the comparison of the epipolar images, the RMSE of the stereo camera was 0.3 pixel more than that of the two single cameras, but the effect was not significant.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.487-493
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• 1998

Camera calibration is the process of determining the coordinate relationship between a camera image and its real world space. Accurate calibration of a camera is necessary for the applications that involve quantitative measurement of camera images. However, if the camera plane is parallel or near parallel to the calibration board on which 2 dimensional objects are defined(this is called "ill-conditioned"), existing solution procedures are not well applied. In this paper, we propose a neural network-based approach to camera calibration for 2D images formed by a mono-camera or a pair of cameras. Multi-layer perceptrons are developed to transform the coordinates of each image point to the world coordinates. The validity of the approach is tested with data points which cover the whole 2D space concerned. Experimental results for both mono-camera and stereo-camera cases indicate that the proposed approach is comparable to Tsai's method［8］. Especially for the stereo camera case, the approach works better than the Tsai's method as the angle between the camera optical axis and the Z-axis increases. Therefore, we believe the approach could be an alternative solution procedure for the ill -conditioned camera calibration.libration.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1997.03a
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• pp.207-212
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• 1997

In estimating the formability of sheet metal, the stereo vision system contributes the accuracy of strain of sheet metal, the convenience in measuring the strain of sheet metal, and the handiness in preparing the forming limit diagram by calculating the 3D values and strain of sheet metal. The algorithm has been developed so that the 3D-coordinate values of sheet metal could be calculated by image processing which is composed of camera calibration, and the stereo matching of images in two viewpoints. By comparing with experiments, the possibility and the convenience of algorithm has been verified, which could calculate the 3D-coordinate values of sheet metal automatically by using the preprocessing of the original image of sheet metal, which had the noise before adjusting the camera calibration and the stereo matching algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.5
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• pp.383-389
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• 2000

This paper presents a stereo camera system that provides a Pair of stereo images using a Biprism. The equivalent of a stereo Pair of images is formed as the left and right halves of a single CCD image. The system is therefore cheap and extremely easy to calibrate since it requires only one CCD camera. An additional advantage of the geometrical set-up is that corresponding features lie on the same scanline automatically, The single camera and Biprism have led to a simple stereo system for which correspondence is very easy and which is accurate for nearby objects in a small field of view. Since we use only a single lens, calibration of the system is greatly simplified. Given the parameters in the Biprism-stereo camera system, we can reconstruct the 3-D structure using only the disparity between the corresponding points.