• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.13 no.10
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• pp.1089-1097
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• 2002

In this paper, the novel shipboard Active Phased Array Antenna(APAA) system for maritime mobile satellite communications is introduced. The antenna uses novel technologies like wide range hybrid tracking, single antenna elements with both of Rx and Tx, asymmetrical array structure, interference isolation between Rx and Tx, and error correction method from frequency scan effect. The antenna has single aperture for both of Rx and Tx with 32 $\times$ 4 two-dimensional array. The antenna has two beams. Its frequencies are 7.25 ~ 7.75 GHz for Rx and 7.9 ~ 8.4 GHz for Tx. The antenna gains are 35.4 dBi for Rx and 35.7 dBi for Tx, those are 54 % of efficiency. The electrically steering ranges are $\pm$35$^{\circ}$ of elevation direction and $\pm$4$^{\circ}$ of azimuth direction. The mechanical control ranges at hybrid tracking capability are continuous 360$^{\circ}$ of azimuth direction and $\pm$10$^{\circ}$ of elevation direction. The antenna has 2.2$^{\circ}$ of 3 dB beamwidth, -14 dB of sidelobe level, and 21 dB of cross-pol suppression. The antenna performance was measured by near field measurement set. Its system performance was tested on the ship motion simulator and with the satellite transponder simulator. The test result showed that its tracking error was within -3 dB from its peak gain under motion condition. The antenna system was tested by real modulated Direct Broadcasting Satellite(DBS) signals to check its communication processing function.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.12
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• pp.1297-1307
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• 2009

The purpose of this paper is to propose a detection algorithm and a tracking algorithm based on silent time using MB-OFDM UWB(Multi-Band Orthogonal Frequency Division Multiplexing Ultra Wide Band) receiver in order to satisfy DAA(Detect And Avoid) regulation of Korea to permit UWB in 3.1~4.8 GHz. In DAA regulation of Korea, if UWB device receives a signal more than -80 dBm/MHz from the victim system during UWB operation, the UWB system should avoid the collision within 2 sec. In this paper, we proposed the detection algorithm to detect the victim signal received by －80 dBm/MHz for the avoidance process that changes the operating UWB frequency to other UWB frequency and the subcarrier tracking algorithm to follow up the subcarrier positions of the victim signal for the tonenulling avoidance process that decreases the TX power of subcarriers occupied by the victim signal by -70 dBm/MHz. The performance of the detection algorithm and the tracking algorithm suggested in this paper is verified in simulation results considering various conditions.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.158-163
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• 2009

In recent years, there has been increased interest in characterizing and extracting 3D information from 2D images for human tracking and identification. In this paper, we propose a single view-based framework for robust estimation of height and position. In the proposed method, 2D features of target object is back-projected into the 3D scene space where its coordinate system is given by a rectangular marker. Then the position and the height are estimated in the 3D space. In addition, geometric error caused by inaccurate projective mapping is corrected by using geometric constraints provided by the marker. The accuracy and the robustness of our technique are verified on the experimental results of several real video sequences from outdoor environments.

• Journal of KIBIM
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• v.5 no.2
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• pp.46-54
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• 2015

Vision-based tracking has been proposed as a means to efficiently track a large number of construction resources operating in a congested site. In order to obtain 3D coordinates of an object, it is necessary to employ stereo-vision theories. Detecting and tracking of multiple objects require an entity matching process that finds corresponding pairs of detected entities across the two camera views. This paper proposes an efficient way of entity matching for tracking of construction workers. The proposed method basically uses epipolar geometry which represents the relationship between the two fixed cameras. Each pixel coordinate in a camera view is projected onto the other camera view as an epipolar line. The proposed method finds the matching pair of a worker entity by comparing the proximity of the all detected entities in the other view to the epipolar line. Experimental results demonstrate its suitability for automated entity matching for 3D vision-based tracking of construction workers.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5B
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• pp.557-562
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• 2006

In order to predict the dispersion of suspended sediment arising from dredging operation in port and navigation channel, a hybrid model for dispersive transport of turbidity plume was developed using Lee's(1998) hybrid method. Using hybrid modeling scheme advection-diffusion equation was solved by the forward particle-tracking method for advection process and by the fixed Eulerian grid method for diffusion process. To examine numerical model simulation in accuracy, the simulated results for 1-D, 2-D, and 3-D cases were compared with the analytical solutions including Kuo, et al's (1985) 3-D mathematical model. The model results were in a good agreement with the analytical solutions and mathematical model for the dispersion of turbidity plume.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.499-508
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• 2023

In this paper, we propose a technique to estimate the coordinates of feature points existing on a 2D planar object in the three dimensional space. The proposed method detects multiple 3D features from the image, and excludes those which are not located on the plane. The proposed technique estimates the planar homography between the planar object in the 3D space and the camera image plane, and computes back-projection error of each feature point on the planar object. Then any feature points which have large error is considered as off-plane points and are excluded from the feature estimation phase. The proposed method is archived on the basis of the planar homography without any additional sensors or optimization algorithms. In the expretiments, it was confirmed that the speed of the proposed method is more than 40 frames per second. In addition, compared to the RGB-D camera, there was no significant difference in processing speed, and it was verified that the frame rate was unaffected even in the situation that the number of detected feature points continuously increased.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.70.1-70
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• 2001

Recently, research of visual control is getting more essential in robotic application, and acquiring 3D informations from the 2D images is becoming more important with development of vision system. For this application, we propose the effective way of controlling stereo vision tracking system for target tracking and calculating distance between target and camera. In this paper we address improved controller using dual-loop visual servo which is more effective compared with using single-loop visual servo for stereo vision tracking system. The speed and the accuracy for realizing a real time tracking are important. However, the vision processing speed is too slow to track object in real time by using only vision feedback data. So we use another feedback data from controller parts which offer state feedback ...

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.2
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• pp.217-226
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• 2006

Extraction and tracking objects are fundamental and important steps of the digital image processing and computer vision. Many algorithms about extracting and tracking objects have been developed. In this research, a method is suggested for tracking a moving object using a pair of CCD cameras and calculating the coordinate of the moving object. A 1/100 miniature of soccer field was made to apply the developed algorithms. After candidates were selected from the acquired images using the RGB value of a moving object (soccer ball), the object was extracted using its size (MBR size) among the candidates. And then, image coordinates of a moving object are obtained. The real-time position of a moving object is tracked in the boundary of the expected motion, which is determined by centering the moving object. The 3D position of a moving object can be obtained by conducting the relative orientation, absolute orientation, and space intersection of a pair of the CCD camera image.

• Journal of KIISE:Software and Applications
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• v.35 no.12
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• pp.780-788
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• 2008

Modeling hand poses and tracking its movement are one of the challenging problems in computer vision. There are two typical approaches for the reconstruction of hand poses in 3D, depending on the number of cameras from which images are captured. One is to capture images from multiple cameras or a stereo camera. The other is to capture images from a single camera. The former approach is relatively limited, because of the environmental constraints for setting up multiple cameras. In this paper we propose a method of reconstructing 3D hand poses from a 2D input image sequence captured from a single camera by means of Belief Propagation in a graphical model and recognizing a finger clicking motion using a hidden Markov model. We define a graphical model with hidden nodes representing joints of a hand, and observable nodes with the features extracted from a 2D input image sequence. To track hand poses in 3D, we use a Belief Propagation algorithm, which provides a robust and unified framework for inference in a graphical model. From the estimated 3D hand pose we extract the information for each finger's motion, which is then fed into a hidden Markov model. To recognize natural finger actions, we consider the movements of all the fingers to recognize a single finger's action. We applied the proposed method to a virtual keypad system and the result showed a high recognition rate of 94.66% with 300 test data.

• Journal of Advanced Navigation Technology
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• v.20 no.1
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• pp.53-58
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• 2016

In this paper, we propose a novel quadratic Kalman filter based object tracking algorithm using moving pictures. Quadratic Kalman filter, which is introduced recently, has not yet been applied to the problem of 3-dimensional (3-D) object tracking. Since the mapping of a position in 2-D moving pictures into a 3-D world involves non-linear transformation, appropriate algorithm must be chosen for object tracking. In this situation, the quadratic Kalman filter can achieve better accuracy than extended Kalman filter. Under the same conditions, we compare extended Kalman filter, unscented Kalman filter and sequential importance resampling particle filter together with the proposed scheme. In conculsion, the proposed scheme decreases the divergence rate by half compared with the scheme based on extended Kalman filter and improves the accuracy by about 1% in comparison with the one based on unscented Kalman filter.