• Journal of the Korean Society for Precision Engineering
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• v.14 no.7
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• pp.59-66
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• 1997

A general procedure for a motion capture and mimic system has been delineated. Utilizing sensors operated in the magnetic fields, complicated and optimized movements are easily digitized to analyze and repreduce. The system consists of a motion capture module, a motion visualization module, a motion plan module, a motion mimic module, and a GUI module. Design concepts of the system are modular, open, and user friendly to ensure the overall system performance. Custom-built and/or off-the-shelf modules are ease- ly integrated into the system. With modifications, this procedure can be applied for complicated motion controls. This procedure is implemented on tracking a head and balancing a pole. A neural controller based on this control scheme dtilizing human motions can easily evolve from a small amount of learning data.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.507-512
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• 2007

This paper presents a tracking filter with ship's motion compensation for a ship-borne radar tracking system. The ship's maneuver is described by displacement and rotational motions in the ship-centered east-north frame. The first order Taylor series approximation of the measurement error covariance of the converted measurement is derived in the ship-centered east-north frame. The ship's maneuver is compensated by incorporating the measurement error covariance of the converted measurement and displacement of the position state in the tracking filter. The simulation results via 500 Monte-Carlo runs show that the proposed method follows the target successfully and provides consistent tracking performance during ship's maneuvers while the conventional tracking filter without ship motion compensation fails to track during such periods.

• Proceedings of the Korea Contents Association Conference
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• 2004.05a
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• pp.396-400
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• 2004

In this study, we have proposed the tracking system of single moving object. The tracking system was estimated motion using differential image, and than track the moving object by controlled Pan/Tilt device of camera. Proposed tracking system is devided into image acquisition and preprocessing phase, motion estimation phase and object tracking phase. To estimation the motion, differential image method was used. In the binary differential image, decision of threshold value was used adaptive method. And in grouping the object area, block_based recursive labeling algorithm was used. As a result of experiment, motion of moving object can be estimated. The result of tracking, object was not lost and object was tracked correctly.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.2
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• pp.15-19
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• 2008

In this paper, we propose a new algorithm of image depth detection using motion estimation and object tracking. In industry, robots are used for automobile, conveyer system, etc. But, these have much necessary time. Thus, in this paper, we develop the efficient method of image depth detection based on motion estimation and object tracking.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11a
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• pp.235-240
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• 2001

A four degrees of freedom (dof) motion platform for bicycle simulator is developed. The motion platform, capable of the vertical linear and three angular motions, is designed based on analysis of the typical motion characteristics revealed by the existing six dof bicycle simulator. The platform essentially consists of two parts： the three dof parallel manipulator, consisting of a moving platform, a fixed base and three actuators, and the turntable to generate the yaw motion. The nonlinear kinematics and dynamics of the three dof parallel manipulator with multiple closed loop chains are analyzed for tracking control of the motion platform. The tracking performances of the three control schemes are experimentally compared： the computed torque method (CTM), the sliding mode control (SMC) and the PD control. The CTM and SMC, incorporated with the system dynamics model, are found to be equally better in performance than the PD controller, irrespective of the presence of external disturbance.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.1 s.232
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• pp.139-144
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• 2005

A vehicle cruise control algorithm using an Interacting Multiple Model (IMM)-based Multi-Target Tracking (MTT) method has been presented in this paper. The vehicle cruise control algorithm consists of three parts; track estimator using IMM-Probabilistic Data Association Filter (PDAF), a primary target vehicle determination algorithm and a single-target adaptive cruise control algorithm. Three motion models; uniform motion, lane-change motion and acceleration motion. have been adopted to distinguish large lateral motions from longitudinal motions. The models have been validated using simulated and experimental data. The improvement in the state estimation performance when using three models is verified in target tracking simulations. The performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. These simulations show system response that is more realistic and reflective of actual human driving behavior.

• Journal of information and communication convergence engineering
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• v.2 no.1
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• pp.52-57
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• 2004

In this paper, we propose a panorama-based object tracking scheme for wide-view surveillance systems that can detect and track moving objects with a pan-tilt camera. A dynamic mosaic of the background is progressively integrated in a single image using the camera motion information. For the camera motion estimation, we calculate affine motion parameters for each frame sequentially with respect to its previous frame. The camera motion is robustly estimated on the background by discriminating between background and foreground regions. The modified block-based motion estimation is used to separate the background region. Each moving object is segmented by image subtraction from the mosaic background. The proposed tracking system has demonstrated good performance for several test video sequences.

• Journal of Information Display
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• v.6 no.4
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• pp.16-25
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• 2005

In this paper, a new 3D object tracking system using the disparity motion vector (DMV) is presented. In the proposed method, the time-sequential disparity maps are extracted from the sequence of the stereo input image pairs and these disparity maps are used to sequentially estimate the DMV defined as a disparity difference between two consecutive disparity maps Similarly to motion vectors in the conventional video signals, the DMV provides us with motion information of a moving target by showing a relatively large change in the disparity values in the target areas. Accordingly, this DMV helps detect the target area and its location coordinates. Based on these location data of a moving target, the pan/tilt embedded in the stereo camera system can be controlled and consequently achieve real-time stereo tracking of a moving target. From the results of experiments with 9 frames of the stereo image pairs having 256x256 pixels, it is shown that the proposed DMV-based stereo object tracking system can track the moving target with a relatively low error ratio of about 3.05 % on average.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.172.5-172
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• 2001

Target Motion Analysis(TMA) for Passive Sonar Systems with bearing-only measurements needs to enhance system observability to improve target tracking performance by ownship maneuvering. However, tracking problem incurred by weak observaility result in slow convergence of the target estimates. On the other hand, active sonar systems do not have problem associated with system observaility. However, it drawback related to system survivability. In this paper, the algorithm that could be used in Active/passive Mixed-Mode Sonar Systems is proposed to analyze maneuvering target motion and to improve TMA performance. The proposed TMA algorithm is tested by a series of computer simulation runs and the results ...

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1203-1204
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• 2008

In this paper, a new stereo object tracking system using the disparity motion vector is proposed. In the proposed method, the time-sequential disparity motion vector can be estimated from the disparity vectors which are extracted from the sequence of the stereo input image pair and then using these disparity motion vectors, the area where the target object is located and its location coordinate are detected from the input stereo image. Basing on this location data of the target object, the pan/tilt embedded in the stereo camera system can be controlled and as a result, 3D tracking of the target object can be possible.