• Journal of the Institute of Electronics Engineers of Korea TC
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• v.37 no.8
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• pp.11-23
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• 2000

Head-eye calibration is a process for estimating the unknown orientation and position of a camera with respect to a mobile platform, such as a robot wrist. We present a new head-eye calibration technique which can be applied for platforms with rather limited motion capability In particular, the proposed calibration technique can be applied to find the relative orientation of a camera mounted on a linear translation platform which does not have rotation capability. The algorithm find the rotation using a calibration data obtained from pure Translation of a camera along two different axes We have derived a calibration algorithm exploiting the rectification technique in such a way that the rectified images should satisfy the epipolar constraint. We present the calibration procedure for both the rotation and the translation components of a camera relative to the platform coordinates. The efficacy of the algorithm is demonstrated through simulations and real experiments.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.5
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• pp.35-44
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• 2007

Since the omnidirectional camera system with a very large field of view could take many information about environment scene from few images, various researches for calibration and 3D reconstruction using omnidirectional image have been presented actively. Most of line segments of man-made objects we projected to the contours by using the omnidirectional camera model. Therefore, the corresponding contours among images sequences would be useful for computing the camera transformations including rotation and translation. This paper presents a novel two step minimization method to estimate the extrinsic parameters of the camera from the corresponding contours. In the first step, coarse camera parameters are estimated by minimizing an angular error function between epipolar planes and back-projected vectors from each corresponding point. Then we can compute the final parameters minimizing a distance error of the projected contours and the actual contours. Simulation results on the synthetic and real images demonstrated that our algorithm can achieve precise contour matching and camera motion estimation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.6A
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• pp.458-463
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• 2012

In this paper, we propose a direct depth map acquisition method for the convergence camera array as well as the parallel camera array. The conventional methods perform image rectification to reduce complexity and improve accuarcy. However, image rectification may lead to unwanted consequences for the convergence camera array. Thus, the proposed method excludes image rectification and directly extracts depth values using the epipolar constraint. In order to acquire a more accurate depth map, occlusion detection and handling processes are added. Reasonable depth values are assigned to the obtained occlusion region by the distance and color differences from neighboring pixels. Experimental results show that the proposed method has fewer limitations than the conventional methods and generates more accurate depth maps stably.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.44-56
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• 2008

Previous hardware devices to capture human motion have many limitations; expensive equipment, complexity of manipulation or constraints of human motion. In order to overcome these problems, real-time motion capture algorithms based on computer vision have been actively proposed. This paper presents an efficient analysis method of multiple view images for real-time motion capture. First, we detect the skin color regions of human being, and then correct the image coordinates of the regions by using camera calibration and epipolar geometry. Finally, we track the human body part and capture human motion using kalman filter. Experimental results show that the proposed algorithm can estimate a precise position of the human body.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.9
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• pp.64-75
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• 1993

This paper proposes a recovering technique of the elevation map by stereo modeling of the aerial image sequence which is transformed based on the aircraft situation. The area-based stereo matching method is simulated and the various parameters are experimentally chosen. In a depth extraction step, the depth is determined by solving the vector equation. The equation is suitable for stereo modeling of aerial images which do not satisfy the epipolar constraint. Also, the performance of the conventional feature-based matching scheme is compared. Finally, techniques analyzing the accuracy of the recovered elevation map (REM) are described. The analysis includes the error estimation for both height and contour lines, where the accuracy is based on the measurements of deviations from the estimates obtained manually. The experimental results show the efficiency of the proposed technique.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1749-1752
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• 2005

For online high accurate reconstruction of an object from an visual information, a linear reconstruction method for multiple images is popular. Basically this method needs many cameras or many different screen shots from different view points. This method, however, has the benefit of less calculation and is adequate for a real time application by comparing other popular method. In this paper, online reconstruction system using more than three cameras is treated. An evaluation method of cameras' position, and of the number is derived for the linear reconstruction method. To decrease errors that are caused from skew of lens, positional error between corresponding points is taken into consideration on the evaluation. The proposed evaluation method enables estimation of the adequate number of cameras and then of feasible view locations. Additionally, repeating search of epipolar lines enables estimation of the hidden point. Comparing with result of an average error analysis, it was confirmed that the proposed methods works effectively.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.183-186
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• 2003

A vision sensor should be calibrated prior to infer a Euclidian shape reconstruction. A point to point calibration. also referred to as a hard calibration, estimates calibration parameters by means of a set of 3D to 2D point pairs. We proposed a new method for determining a set of 3D to 2D pairs for the structured light hard calibration. It is simply determined based on epipolar geometry between camera image plane and projector plane, and a projector calibrating grid pattern. The projector calibration is divided two stages; world 3D data acquisition Stage and corresponding 2D data acquisition stage. After 3D data points are derived using cross ratio, corresponding 2D point in the projector plane can be determined by the fundamental matrix and horizontal grid ID of a projector calibrating pattern. Euclidian reconstruction can be achieved by linear triangulation. and experimental results from simulation are presented.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.224-228
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• 1997

Computer vision system become more important as the researches on inspection systems, intelligent robots , diagnostic medical systems is performed actively. In this paper, 3D measuring system is developed by using stereo vision. The relation between left image and right image is obtained by using 8 point algorithm, and fundamental matrix, epipole and 3D reconstruction algorithm are used to measure 3D dimensions. 3D measuring system was developed by Visual Basic, in which 3D coordinates would be obtained by simple mouse clicks. This software would be applied to construction area, home interior system, rapid measuring system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.732-736
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• 2009

In this paper we focus on EPI (Epipolar-Plane Image), the horizontal cross section of Ray-Space, and we propose a novel method that chooses objects we want and edits scenes by using multi-view images. On the EPI acquired by camera arrays uniformly distributed along a line, all the objects are represented as straight lines, and the slope of straight lines are decided by the distance between objects and camera plane. Detecting a straight line of a specific slope and removing it mean that an object in a specific depth has been detected and removed. So we propose a scheme to make a layer of a specific slope compete with other layers instead of extracting layers sequentially from front to back. This enables an effective removal of obstacles, object manipulation and a clearer 3D scene with what we want to see will be made.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3721-3737
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• 2015

3D reconstruction based on binocular data is significant to machine vision. In our method, we propose a new and high efficiency 3D reconstruction approach by using a consumer camera aiming to: 1) address the configuration problem of dual camera in the binocular reconstruction system; 2) address stereo matching can hardly be done well problem in both time computing and precision. The kernel feature is firstly proposed in calibration stage to rectify the epipolar. Then, we segment the objects in the camera into background and foreground, for which system obtains the disparity by different method: local window matching and kernel feature-based matching. Extensive experiments demonstrate our proposed algorithm represents accurate 3D model.