• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.660-665
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• 1993

Neural networks are used in the framework of sensorbased tracking control of robot manipulators. They learn by practice movements the relationship between PSD ( an analog Position Sensitive Detector) sensor readings for target positions and the joint commands to reach them. Using this configuration, the system can track or follow a moving or stationary object in real time. Furthermore, an efficient neural network architecture has been developed for real time learning. This network uses multiple sets of simple backpropagation networks one of which is selected according to which division (corresponding to a cluster of the self-organizing feature map) in data space the current input data belongs to. This lends itself to a very fast training and processing implementation required for real time control.

• International Journal of Advanced Culture Technology
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• v.4 no.4
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• pp.81-86
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• 2016

In this paper, we propose a simple and effective vision-based tracking controller design for autonomous object tracking using multicopter. The multicopter based automatic tracking system usually unstable when the object moved so the tracking process can't define the object position location exactly that means when the object moves, the system can't track object suddenly along to the direction of objects movement. The system will always looking for the object from the first point or its home position. In this paper, PID control used to improve the stability of tracking system, so that the result object tracking became more stable than before, it can be seen from error of tracking. A computer vision and control strategy is applied to detect a diverse set of moving objects on Raspberry Pi based platform and Software defined PID controller design to control Yaw, Throttle, Pitch of the multicopter in real time. Finally based series of experiment results and concluded that the PID control make the tracking system become more stable in real time.

• Journal of Korea Multimedia Society
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• v.23 no.10
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• pp.1236-1249
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• 2020

In a most recent object tracking research work, applying Convolutional Neural Network and Recurrent Neural Network-based strategies become relevant for resolving the noticeable challenges in it, like, occlusion, motion, object, and camera viewpoint variations, changing several targets, lighting variations. In this paper, the LSTM Network-based Tracking association method has proposed where the technique capable of real-time multi-object tracking by creating one of the useful LSTM networks that associated with tracking, which supports the long term tracking along with solving challenges. The LSTM network is a different neural network defined in Keras as a sequence of layers, where the Sequential classes would be a container for these layers. This purposing network structure builds with the integration of tracking association on Keras neural-network library. The tracking process has been associated with the LSTM Network feature learning output and obtained outstanding real-time detection and tracking performance. In this work, the main focus was learning trackable objects locations, appearance, and motion details, then predicting the feature location of objects on boxes according to their initial position. The performance of the joint object tracking system has shown that the LSTM network is more powerful and capable of working on a real-time multi-object tracking process.

• The Journal of Korean Institute of Information Technology
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• v.17 no.8
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• pp.75-83
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• 2019

In this paper, we propose a method that can detect and trace the end point of real - time reinforcement steel to various environmental conditions of industrial field by using Median flow and Depth information. We proposed a method to derive two steel end points by using Median filter, Binarization, Morphology, and Blob algorithm on image depth information. The coordinates of the final position were determined by comparing the coordinates of the reinforcement steel endpoints detected in the Depth image and the position tracking coordinates of the reinforcement steel using Median Flow. As a result, when the existing Median Flow method was used, the success rate of the final position determination of reinforcement steel of 75% was increased to 95% when the Depth of reinforcement steel was used.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.4
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• pp.45-54
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• 2004

In this paper, a view point tracking system has been realized for outdoor augmented reality including broad area monitoring. Since the surroundings of the moving view point are changing, it is necessary to track the position and observation moment of the view point system for consistency between real and virtual images. For this reason, the GPS(Global Positioning System) is applied to the realized system for tracking the information on position and direction of the moving system. In addition, an optical position tracking system that is able to track view point in a limited area is used, because the local tracking system has to trace the image variation, seen to the observer in a moving vehicle, at a particular position and time. It was found that the realized outdoor augmented reality system, which combined the virtual information tracked in real time with the real image, can be very practical in various application area.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.52-58
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• 2002

This Paper describes the method of real time object tracking using variable searching window. Monitoring systems require real time object tracking in video, efficiencies depend on environment of monitoring target. To get a position of object using a difference between background image and input image, the system extracts contour and centroid of the object. This method track motion of object using variable searching window from size and position of object. The background imgaes and camera are limited as fixed environment. The test result of proposed method Is 17-23FPS, this shows more fast process speed than average(10-14FPS) of existing object tracking method.

• Transactions of The Korea Fluid Power Systems Society
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• v.5 no.4
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• pp.26-31
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• 2008

This paper deals with the issue of position tracking control of a clamp-cylinder for injection moulding machine with electric-hydrostatic drives. A fixed displacement pump is utilized in combination with AC motor in order to directly control a clamp-cylinder. A clamp-cylinder may be required to operate under a variety of operating conditions. Therefore, robust control performance is important in position tracking control applications. In order to accommodate mismatches between the real plant and the model used for controller design, discrete-time sliding mode control is developed by combining a velocity feedforward loop. From tracking control experiments, it is shown that significant reduction in position tracking error is achieved through the use of sliding mode control.

• Journal of Ubiquitous Convergence Technology
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• v.1 no.1
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• pp.3-8
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• 2007

This paper presents a set of techniques used in a real-time visual surveillance system. The system is implemented on a low-cost embedded DSP platform that is designed to work with stationary video sources. It consists of detection, a tracking and a classification module. The detector uses a statistical method to establish the background model and extract the foreground pixels. These pixels are grouped into blobs which are classified into single person, people in a group and other objects by the dynamic periodicity analysis. The tracking module uses mean shift algorithm to locate the target position. The system aims to control the human density in the surveilled scene and detect what happens abnormally. The major advantage of this system is the real-time capability and it only requires a video stream without other additional sensors. We evaluate the system in the real application, for example monitoring the subway entrance and the building hall, and the results prove the system's superior performance.

• 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 Korea Academia-Industrial cooperation Society
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• v.11 no.1
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• pp.96-100
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• 2010

In this paper we present a position tracking system that checks the locations of moving targets in real-time. The system confirms that unknown object invades in watch area using 2 infrared sensors and detect the distance from each sensor to object using 4 ultrasonic sensors, and calculate the position of moving object in x-y coordinate. We specially present an algorithm that decide the location of target in case of target is detected in 2 sensors because of radiation beam width of ultrasonic sensor. We established the algorithm to hardware system and tested the system within a laboratory, and confirmed that the designed system tracked an object exactly in real-time.