• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2C
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• pp.246-253
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• 2010

In this paper, a method of removing the space skew and cross-talk cancellation is proposed where the self-generated signals from the subject are used to obtain the subject's location. In the proposed method, the good spatial sound image is maintained even when the listener moves from the sweet spot. Two major parts of the proposed method are as follows: listener position tracking using the stimuli from the subject and removal of the space skew and cross-talk signals. Listener position tracking is achieved by estimation of the time difference of arrival (TDoA). The position of the listener is then computed using the Talyer-series estimation method. The head-related transfer functions (HRTF) are used to remove the space skew and cross-talk signals, where the direction of the HRTF is given by the one estimated from the listener position tracking. The performance evaluation is carried out on the signals from the 100 subjects that are composed of the 50 female and 50 male subjects. The positioning accuracy is achieved by 70%~90%, under the condition that the mean squared positioning error is less than $0.07m^2$. The subjective listening test is also conducted where the 27 out of the 30 subjects are participated. According to the results, 70% of the subjects indicates that the overall quality of the reproduced sound from the proposed method are improved, regardless of the subject's position.

• Spatial Information Research
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• v.19 no.3
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• pp.53-62
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• 2011

Spatial information services in indoor space are an im portant application area of GIS as in outdoor space. Unlike in outdoor space, a position in indoor space is specified by a symbolic code such as room number, rather than coordinate. Therefore tracking in indoor space is no longer a prediction of coordinates but a symbolic estimation on the current position of a moving object. In this paper, we propose a framework for tracking moving objects in indoor symbolic space with RFID sensors. First, we introduce the concepts of indoor symbolic space and tracking in indoor symbolic space, and define the accessibility graph for trackable indoor symbolic space. Second, we propose a deployment method of RFID readers and a construction algorithm of accessibility graph for trackable indoor symbolic space. Third, a tracking method is proposed for moving objects in symbolic indoor space with RFID sensors. Finally, we present an implementation exmaple and the result of experiment with real data to validate the proposed method.

• Journal of Advanced Navigation Technology
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• v.14 no.2
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• pp.272-277
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• 2010

AR(Augmented Reality) needs medium between real and virtual, world, and recognition techniques are necessary to track an object continuously. Optical tracking using marker is mainly used, but it takes time and is inconvenient to attach marker onto the target objects. Therefore, many researchers try to develop markerless tracking techniques nowaday. In this paper, we extract features and 3D position from 3D objects and suggest realtime tracking based on these features and positions, which do not use just coplanar features and 2D position. We extract features using SURF, get rotation matrix and translation vector of 3D object using POSIT with these features and track the object in real time. If the extracted features are nor enough and it fail to track the object, then new features are extracted and re-matched to recover the tracking. Also, we get rotation in matrix and translation vector of 3D object using POSIT and track the object in real time.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.1
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• pp.1226-1230
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• 2001

Multi-target tracking systems need to tracking several targets simultaneously. To track a target among the measurements of several targets, data association is needed. In this paper, a method using the cou-pled confidence region of predicted target position is proposed. The proposed method shows good performance in simulations of multi-target tracking systems.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2701-2706
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• 2003

This paper describes weld seam tracking and error compensation methods of automatic plasma arc welding system designed for the corrugation panel that consists of a linear section and a curved section with various curvatures. Realizing automatic welding system, we are faced with two problems. One is a precise seam tracking and the other is an arc length control. Due to the complexity of the panel shape, it is difficult to find a seam and operate a torch manually in the welding process. So, laser vision sensor for seam tracking is equipped for sensing the seam position and controlling the height of a torch automatically. To attain more precise measurement of an arc length, we measure the 3D shape of the panel and analyze error factors according to the various panel states and caused errors are predicted through the welding process. Using that result, compensation algorithm is added to that of arc length control and real time error compensation is achieved. The result shows that these two methods work effectively.

• International Journal of Control, Automation, and Systems
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• v.6 no.5
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• pp.689-701
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• 2008

In this paper, a fully adaptive feedforward feedback synchronized tracking control approach is developed for precision tracking control of 6 degree of freedom (6DOF) Stewart Platform. The proposed controller is designed in decentralized form for implementation simplicity. Interconnections among different subsystems and gravity effect are eliminated by the feedforward control action. Feedback control action guarantees the stability of the system. The gains of the proposed controller can be updated on line without requiring any prior knowledge of Stewart Platform manipulator. Thus the control approach is claimed to be fully adaptive. By employing cross-coupling error technology, the proposed approach can guarantee both of position error and synchronization error converge to zero asymptotically. Because the actuators work in synchronous manner, the tracking performances are improved. The corresponding stability analysis is also presented in this paper. Finally, simulation is demonstrated to verify the effectiveness of the proposed approach.

• ETRI Journal
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• v.30 no.6
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• pp.774-782
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• 2008

An operational orbit determination (OD) and prediction system for the geostationary Communication, Ocean, and Meteorological Satellite (COMS) mission requires accurate satellite positioning knowledge to accomplish image navigation registration on the ground. Ranging and tracking data from a single ground station is used for COMS OD in normal operation. However, the orbital longitude of the COMS is so close to that of satellite tracking sites that geometric singularity affects observability. A method to solve the azimuth bias of a single station in singularity is to periodically apply an estimated azimuth bias using the ranging and tracking data of two stations. Velocity increments of a wheel off-loading maneuver which is performed twice a day are fixed by planned values without considering maneuver efficiency during OD. Using only single-station data with the correction of the azimuth bias, OD can achieve three-sigma position accuracy on the order of 1.5 km root-sum-square.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.6
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• pp.213-221
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• 2003

This paper describes a method of lane tracking by means of a vision system which includes vehicle control and modeling. Lane tracking is considered one of the important technologies in an unmanned vehicle and mobile robot system. The current position and condition of the vehicle are calculated from an image processing method by a CCD camera. We deal with lane tracking as follows. First, vehicle control is included in the road model, and lateral and longitudinal controls. Second, the image processing method deals with the lane detection method, image processing algerian, and filtering method. Finally, this paper proposes a correct method for lane detection through a vehicle test by wireless data communication.

• Journal of Korea Multimedia Society
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• v.10 no.7
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• pp.827-837
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• 2007

Conventional color-based object tracking using Mean Shift algorithm does not provide appropriate result when initial color distribution disappears. In this paper we propose a tracking algorithm that updates the object color sample when the color is changing. Mean Shift analysis is first used to derive the object candidate with maximum increase in density direction from current position. The color information of object is updated iteratively. The proposed algorithm achieves accurate tracking of objects when initial color samples are changed and finally disappeared. The validity of the effective approach is illustrated by the experimental results.

• Journal of Electrical Engineering and information Science
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• v.3 no.2
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• pp.230-238
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• 1998

When size and shape of moving object have been changed, a correlator often accumulates walk-off error. A success of correlation-based tracking largely depends on choosing suitable window size and position and thus transferring the proper reference image to the next frame. For this, we propose the Adaptive Window Algorithm with Four-Direction Sizing Factors (AWA-FSF) for fast adjusting a reference region to enhance reliability of correlation-based image tracking in complex cluttered environments. Since the AWA-FSF is capable of adjusting a reference image size more rapidly and properly, we can minimize the influence of complex background and clutter. In addition, we can finely tune the center point of the reference image repeatedly after main tracking process. Thus we have increased stability and reliability of correlation-based image tracking. We tested performance of the AWA-FSF using 45 real image sequences made of over 3400 images and had the satisfied results for most of them.