• KIPS Transactions on Software and Data Engineering
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• v.2 no.11
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• pp.789-794
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• 2013

A vehicle tracking system makes it possible to induce the vehicle movement path for avoiding traffic congestion and to prevent traffic accidents in advance by recognizing traffic flow, monitoring vehicles, and detecting road accidents. To track the vehicles effectively, those which appear in a sequence of video frames need to identified by extracting the features of each object in the frames. Next, the identical vehicles over the continuous frames need to be recognized through the matching among the objects' feature values. In this paper, we identify objects by binarizing the difference image between a target and a referential image, and the labelling technique. As feature values, we use the center coordinate of the minimum bounding rectangle(MBR) of the identified object and the averages of 1D FFT(fast Fourier transform) coefficients with respect to the horizontal and vertical direction of the MBR. A vehicle is tracked in such a way that the pair of objects that have the highest similarity among objects in two continuous images are regarded as an identical object. The experimental result shows that the proposed method outperforms the existing methods that use geometrical features in tracking accuracy.

• Journal of the Ergonomics Society of Korea
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• v.26 no.2
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• pp.149-155
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• 2007

Recently, various devices requiring text input such as mobile phone IPTV, PDA and UMPC are emerging. The frequency of text entry for them is also increasing. This study was focused on the evaluation of Korean text entry interface. Various models to evaluate text entry interfaces have been proposed. Most of models were based on human cognitive process for text input. The cognitive process was divided into two components; visual scanning process and finger movement process. The time spent for visual scanning process was modeled as Hick-Hyman law, while the time for finger movement was determined as Fitts' law. There are three questions on the model-based evaluation of text entry interface. Firstly, are human cognitive processes (visual scanning and finger movement) during the entry of text sequentially occurring as the models. Secondly, is it possible to predict real text input time by previous models. Thirdly, does the human cognitive process for text input vary according to users' text entry speed. There was time gap between the real measured text input time and predicted time. The time gap was larger in the case of participants with high speed to enter text. The reason was found out investigating Eye-Hand Coordination during text input process. Differently from an assumption that visual scan on the keyboard is followed by a finger movement, the experienced group performed both visual scanning and finger movement simultaneously. Arrival Lead Time was investigated to measure the extent of time overlapping between two processes. 'Arrival Lead Time' is the interval between the eye fixation on the target button and the button click. In addition to the arrival lead time, it was revealed that the experienced group uses the less number of fixations during text entry than the novice group. This result will contribute to the improvement of evaluation model for text entry interface.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.55-62
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• 1999

In order to perform a elaborate task like as assembly, manufacturing and so forth of components, tracking control on the trajectory of power coming in contact with a target as well as tracking control on the movement course trajectory of end-effector is indispensable. In this paper, to bring under robust ard accurate control of auto-equipnent systems which disturbance, parameter alteration of system, uncertainty ard so forth exist, neural network controller called dynamic neural processor(DNP) is designed. Also, the learning architecture to compute inverse kinematic coordinates transfonnations in the manirclator of auto-equipnent systems is developed ard the example that DNP can be used is explained The architocture and learning algorithm of the proposed dynamic neural network, the DNP, are described and computer simllations are provided to demonstrate the effectiveness of the proposed learning method using the DNP.he DNP.

• Journal of Korea Multimedia Society
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• v.23 no.1
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• pp.15-23
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• 2020

Recently, the increase in the elderly population due to an aging society has led to a relative increase in senile diseases such as vascular dementia or Alzheimer's disease, and the social burden for rehabilitation has increased. In addition, studies have been conducted for the risk assessment and prevention of musculoskeletal disorders. The purpose of this study is to suggest a system that can be used to help with dementia prevention training by tracking the movement of motion and virtual reality contents for the risk factors of musculoskeletal disorders of the elderly. We propose a training method for preventing dementia through musculoskeletal motion analysis algorithm and virtual reality content. Through motion recognition algorithm based on motion region design, we will track and analyze the moving radius of the target joint. The purpose of this study is to calculate and evaluate scores based on the time to accomplish the goals on virtual reality contents for the prevention of musculoskeletal disorders and the support of dementia prevention training, and the degree of difficulty, and to analyze the correlation between the results of performing K-MMSE and VR contents.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.6
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• pp.1574-1580
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• 2008

In this paper, to bring under robust and accurate control of auto-equipment systems which disturbance, parameter alteration of system, uncertainty and so forth exist, neural network controller called dynamic neural processor(DNP) is designed In order to perform a elaborate task like as assembly, manufacturing and so forth of components, tracking control on the trajectory of power coming in contact with a target as well as tracking control on the movement course trajectory of end-effector is indispensable. Also, the learning architecture to compute inverse kinematic coordinates transformations in the Plants of auto-equipment systems is developed and the example that DNP can be used is explained. The architecture and learning algorithm of the proposed dynamic neural network, the DNP, are described and computer simulations are provided to demonstrate the effectiveness of the proposed learning method using the DNP.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.44 no.3
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• pp.218-228
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• 2008

This paper describes on the real-time tracking of ship's dynamic behavior by AIS information in the coastal waters. The AIS data was received at a land station by using the antenna of AIS receiver mounted on the rooftop of the laboratory, Pukyong National University (PKNU), Busan, Korea, and stored as a NMEA format of serial output sentence of VDM(VHF Data-Link Message) and displayed on the ENC(Electronic Navigational Chart) of a PC-based ECDIS. In this study, the AIS receiver was mainly used to obtain the dynamic information that is necessary to evaluate and track the movement situation of training ship "KAYA" of PKNU in the coastal waters. The change of position with time for the ship turning under the rudder angle of port $30^{\circ}$ was correctly tracked with the turning circle of 940 m in diameter on the ENC of a PC-based ECDIS. Then, the dynamic information of the AIS system was updated every 6.29 seconds under the turning situation for the speed of 10.9 knots and every 21.65 seconds under the situation running at the speed of 11.05 knots on the straight line route of $155^{\circ}$, respectively. In case of AIS target tracking in the inshore zone behind large topographical obstructions, such as mountain and apartment buildings, the update rate of dynamic information was irregularly changed by the existence of land obstacles. However, the position tracking by AIS information under the situation existing no sea obstructions was achieved in real or near real-time and the instant presentation of course alternations for the ship was correctly monitored by using a PC-based ECDIS. From these results, we concluded that the PC-based ECDIS technology and methodology combined with the AIS information can be easily extended and applied to the surveillance and management for the fishing operation of fishing vessels in the coastal zone and in the EEZ fishing grounds.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.105-114
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• 2011

The snake algorithm is widely adopted to track objects by extracting the active contour of the object from background. However, it fails to track the target converging to the background if there exists background whose gradient is greater than that of the pixels on the contour. Also, the contour may shrink when the target moves fast and the snake algorithm misses the boundary of the object in its searching window. To alleviate these problems, we propose an improved algorithm that can track object contour more robustly. Firstly, we propose two external energy functions, the edge energy and the contrast energy. One is designed to give more weight to the gradient on the boundary and the other to reflect the contrast difference between the object and background. Secondly, by computing the motion vector of the contour from the difference of the two consecutive frames, we can move the snake pointers of the previous frame near the region where the object boundary is probable at the current frame. Computer experiments show that the proposed method is more robust to the complicated background than the previously known methods and can track the object with fast movement.

• Korean Journal of Optics and Photonics
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• v.32 no.4
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• pp.153-162
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• 2021

In this article, the design of a variable F-number and triple magnification infrared optical system is described. That is a two-in-one optical system that combines an infrared search and track (IRST) system and an electro-optical tracking system (EOTS), where an afocal optical system is added to the IRST optical system designed already. The performance target is determined by analyzing system performance, and then the specification in the optical system design is calculated. This optical system contains a warm stop making it possible that one optics has two different F/# by cutting the size of aperture, and that is designed to suit this optics. The system satisfies the requirement such as a modulation transfer function (MTF). For operational assessment, the movement of the focusing lens group is analyzed over the change of temperature and target distance. By using this optical system, it is possible to develop equipment having two functions, infrared searching and electro-optical tracking.

• International Journal of Control, Automation, and Systems
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• v.5 no.1
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• pp.15-23
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• 2007

In surveillance, monitoring, and target tracking operations, high-resolution images should be obtained even if the target is in a far distance. Frequent movements of vehicles such as boats degrade the image quality of onboard camera systems. Therefore, stabilizer mechanisms are required to stabilize the line of sight of boatboard camera systems against boat movements. This paper addresses design and implementation of a strapdown boatboard camera stabilizer. A two degree of freedom(DOF)(pan/tilt) robot performs the stabilization task. The main problem is divided into two subproblems dealing with attitude estimation and attitude control. It is assumed that exact estimate of the boat movement is available from an attitude estimation system. Estimates obtained in this way are carefully transformed to robot coordinate frame to provide desired trajectories, which should be tracked by the robot to compensate for the boat movements. Such a practical robotic system includes actuators with fast dynamics(electrical dynamics) and has more degrees of freedom than control inputs. Backstepping method is employed to deal with this problem by extending the control effectiveness.

• Journal of information and communication convergence engineering
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• v.10 no.4
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• pp.390-395
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• 2012

This paper describes an implementation of automatic mutual localization of swarm robots using a particle filter. Each robot determines the location of the other robots using wireless sensors. The measured data will be used for determination of the movement method of the robot itself. It also affects the other robots' self-arrangement into formations such as circles and lines. We discuss the problem of a circle formation enclosing a target that moves. This method is the solution for enclosing an invader in a circle formation based on mutual localization of the multi-robot without infrastructure. We use trilateration, which does require knowing the value of the coordinates of the reference points. Therefore, specifying the enclosure point based on the number of robots and their relative positions in the coordinate system. A particle filter is used to improve the accuracy of the robot's location. The particle filter is operates better for mutual location of robots than any other estimation algorithms. Through the experiments, we show that the proposed scheme is stable and works well in real environments.