• Journal of the Korean Society for Precision Engineering
• /
• v.12 no.8
• /
• pp.156-167
• /
• 1995

In this paper, we propose a 3-D range finding method for situation that stereo camera has small translational motion. Binocular stereo generally tends to produce stereo correspondence errors and needs huge amount of computation. The former drawback is because the additional constraints to regularize the correspondence problem are not always true for every scene. The latter drawback is because they use either correlation or optimization to find correct disparity. We present a method which overcomes these drawbacks by moving the stereo camera actively. The method utilized a motion parallax acquired by monocular motion stereo to restrict the search range of binocular disparity. Using only the uniqueness of disparity makes it possible to find reliable binocular disparity. Experimental results with real scene are presented to demonstrate the effectiveness of this method.

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

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

• Proceedings of the KSME Conference
• /
• 2002.08a
• /
• pp.507-510
• /
• 2002

An algorithm of 3-D particle image velocimetry(3D-PIV) was developed for the measurement of 3-D velocity Held of complex flows. The measurement system consists of two or three CCD camera and one RGB image grabber. Flows size is $1500{\times}100{\times}180(mm)$, particle is Nylon12(1mm) and illuminator is Hollogen type lamp(100w). The stereo photogrammetry is adopted for the three dimensional geometrical mesurement of tracer particle. For the stereo-pair matching, the camera parameters should be decide in advance by a camera calibration. Camera parameter calculation equation is collinearity equation. In order to calculate the particle 3-D position based on the stereo photograrnrnetry, the eleven parameters of each camera should be obtained by the calibration of the camera. Epipolar line is used for stereo pair matching. The 3-D position of particle is calculated from the three camera parameters, centers of projection of the three cameras, and photographic coordinates of a particle, which is based on the collinear condition. To find velocity vector used 3-D position data of the first frame and the second frame. To extract error vector applied continuity equation. This study developed of various 3D-PIV animation technique.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2010.06a
• /
• pp.293-293
• /
• 2010

In this paper, we propose a stereo vision based monitoring concept for passenger's safety on railroad platform. In general, basic concept of stereo image processing technique uses the correlations between left and right images, and extracts additional distance information. It provides easy removal of ambient illumination changes, which has been difficult to achieve with conventional 2D based image processing technique. In the paper, we present developed stereo camera and stereo vision based detection algorithm in order to monitor possible accidents at platform area, and verified the detection performance of proposed system with experimental results.

• Journal of information and communication convergence engineering
• /
• v.9 no.1
• /
• pp.83-88
• /
• 2011

Abstract. Image segmentation is always a challenging task in computer vision as well as in pattern recognition. Nowadays, this method has great importance in the field of stereo vision. The disparity information extracting from the binocular image pairs has essential relevance in the fields like Stereoscopic (3D) Imaging Systems, Virtual Reality and 3D Graphics. The term 'disparity' represents the horizontal shift between left camera image and right camera image. Till now, many methods are proposed to visualize or estimate the disparity. In this paper, we present a new technique to visualize the horizontal disparity between two stereo images based on image segmentation method. The process of comparing left camera image with right camera image is popularly known as 'Stereo-Matching'. This method is used in the field of stereo vision for many years and it has large contribution in generating depth and disparity maps. Correlation based stereo-matching are used most of the times to visualize the disparity. Although, for few stereo image pairs it is easy to estimate the horizontal disparity but in case of some other stereo images it becomes quite difficult to distinguish the disparity. Therefore, in order to visualize the horizontal disparity between any stereo image pairs in more robust way, a novel stereo-matching algorithm is proposed which is named as "Quadtree Segmentation of Pixels Disparity Estimation (QSPDE)".

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.26 no.2
• /
• pp.223-229
• /
• 2017

Recently, robotic bin-picking tasks have drawn considerable attention, because flexibility is required in robotic assembly tasks. Generally, stereo camera systems have been used widely for robotic bin-picking, but these have two limitations: First, computational burden for solving correspondence problem on stereo images increases calculation time. Second, errors in image processing and camera calibration reduce accuracy. Moreover, the errors in robot kinematic parameters directly affect robot gripping. In this paper, we propose a method of correcting the bin-picking error by using trinocular vision system which consists of two stereo cameras andone hand-eye camera. First, the two stereo cameras, with wide viewing angle, measure object's pose roughly. Then, the 3rd hand-eye camera approaches the object, and corrects the previous measurement of the stereo camera system. Experimental results show usefulness of the proposed method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.20 no.9
• /
• pp.45-53
• /
• 2006

This paper proposes a method for an effective intelligent route decision for automatic moving robots(AMR) using a 2D spatial map of a stereo camera system. In this method, information about depth and disparity map are detected in the inputting images of a parallel stereo camera. The distance between the automatic moving robot and the obstacle is detected, and a 2D spatial map is obtained from the location coordinates. Then the relative distances between the obstacle and other objects are deduced. The robot move automatically by effective and intelligent route decision using the obtained 2D spatial map. From experiments on robot driving with 240 frames of stereo images, it was found that the error ratio of the calculated distance to the measured distance between objects was very low, 1.52[%] on average.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.55 no.2
• /
• pp.103-109
• /
• 2006

In this paper, the detection scheme of the spatial coordinates based on stereo camera for a intelligent path planning of an automatic mobile robot is proposed. In the proposed system, face area of a moving person is detected from a left image among the stereo image pairs by using the YCbCr color model and its center coordinates are computed by using the centroid method and then using these data, the stereo camera embedded on the mobile robot can be controlled for tracking the moving target in real-time. Moreover, using the disparity mad obtained from the left and right images captured by the tracking-controlled stereo camera system and the perspective transformation between a 3-D scene. and an image plane, depth information can be detected. Finally, based-on the analysis of these calculated coordinates, a mobile robot system is derived as a intelligent path planning and a estimation.

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