• Journal of Institute of Control, Robotics and Systems
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• v.7 no.5
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• pp.445-453
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• 2001

The multiple targets tracking problem has been one of the main issues in the radar applications area in the last decade. Besides the standard Kalman filtering, various methods including the variable dimen-sion filter, input estimation filter, interacting multiple model(IMM) filter, dederated variable dimension filter with input estimation, etc., have proposed to address the tracking and sensor fusion issues. In this pa- per, two existing tracking algorithm, i.e, the IMM filter and the variable dimension filter with input estima-tion(VDIE), are combined for the purpose of improving the tracking performance for maneuvering targets. To evaluate the tracking performance of the proposed algorithm, three typical maneuvering patterns, i.e., waver, pop-up, and high-diver motions, are defined and are applied to the modified IMM filter as well as the standard IMM filter. The smaller RMS tracking errors, in position and velocity, of the modified IMM filter than the standard IMM filter are demonstrated though computer simulations.

• Smart Structures and Systems
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• v.26 no.1
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• pp.49-61
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• 2020

This paper proposes a novel high performance vibration control device, multiple tuned mass dampers-inerters (MTMDI), to suppress the oscillatory motions of structures. The MTMDI, similar to the MTMD, involves multiple tuned mass damper-inerter (TMDI) units. In order to reveal the basic performance of the MTMDI, it is installed on a single degree-of-freedom (SDOF) structure excited by the ground acceleration, and the dynamic magnification factors (DMF) of the structure-MTMDI system are formulated. The optimization criterion is determined as the minimization of maximum values of the relative displacement's DMF for the controlled structure. Based on the particle swarm optimization (PSO) algorithm to tune the optimum parameters of the MTMDI, its performance has been investigated and evaluated in terms of control effectiveness, strokes, stiffness and damping coefficient, inerter element force, and robustness in frequency domain. Meanwhile, further comparison between the MTMDI with MTMD has been conducted. Numerical results clearly demonstrate the MTMDI outperforms the MTMD in control effectiveness and strokes of mass blocks. Additionally, in the aspects of frequency perturbations on both earthquake excitations and structures, the robustness of the MTMDI is also better than the MTMD.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.1
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• pp.39-46
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• 2006

We propose an global color model based method for tracking motions of multiple human using a networked multiple-camera system in intelligent space as a human-robot coexistent system. An intelligent space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of intelligent space as well. One of the main goals of intelligent space is to assist humans and to do different services for them. In order to be capable of doing that, intelligent space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly. In the environment where many camera modules are distributed on network, it is important to identify object in order to track it, because different cameras may be needed as object moves throughout the space and intelligent space should determine the appropriate one. This paper describes appearance based unknown object tracking with the distributed vision system in intelligent space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.1
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• pp.39-45
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• 2019

We propose an active color model based method for tracking motions of multiple human using a networked multiple-camera system in IoT space as a human-robot coexistent system. An IoT space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of IoT space as well. One of the main goals of IoT space is to assist humans and to do different services for them. In order to be capable of doing that, IoT space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly. In the environment where many camera modules are distributed on network, it is important to identify object in order to track it, because different cameras may be needed as object moves throughout the space and IoT space should determine the appropriate one. This paper describes appearance based unknown object tracking with the distributed vision system in IoT space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.553-556
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• 2005

We present a vision-based hand gesture recognition system for object manipulation in virtual space. Most conventional hand gesture recognition systems utilize a simpler method for hand detection such as background subtractions with assumed static observation conditions and those methods are not robust against camera motions, illumination changes, and so on. Therefore, we propose a statistical method to recognize and detect hand regions in images using geometrical structures. Also, Our hand tracking system employs multiple cameras to reduce occlusion problems and non-synchronous multiple observations enhance system scalability. Experimental results show the effectiveness of our method.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.3
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• pp.308-315
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• 1991

This paper deals with the global dynamic behavior of multiple autonomous mobile robots with suggested navigation strategies within unbounded and bounded spatial domain. We derive some navigation strategies of robots wirh complete detectability with finite range to reach their goal states without collision which is motivated by Coulomb's law regarding repulsive and attractive forces between electrical charges. An analysis of the dynamic behavior of the interacting robots with the suggested navigation strategies under the assumption that communication is not permissible between robots is made and some examples are illustrated by computer simulation. The convergence of robot motions to their goal states under certain conditions is established by considering their global dynamic behavior even when some objects are close to their goal points.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.211-211
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• 2000

The multiple targets tracking problem has been one of main issues in the radar applications area in the last decade. Besides the standard Kalman filtering, various methods including the variable dimension filter, input estimation filter, interacting multiple model (IMM) filter, federated variable dimension filter with input estimation, probable data association (PDA) filter etc. have been proposed to address the tracking and sensor fusion issues. In this paper, two existing tracking algorithms, i.e. the IMMPDA filter and the variable dimension filter with input estimation (VDIE), are combined for the purpose of improving the tracking performance of maneuvering targets in clutter. To evaluate the tracking performance of the proposed algorithm, three typical maneuvering patterns i.e. Waver, Pop-Up, and High-Diver motions, are defined and are applied to the modified IMMPDA filter considered as well as the standard IMM filter. The smaller RMS tracking errors, in position and velocity, of the modified IMMPDA filter than the standard IMM filter are demonstrated through computer simulations.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1347-1349
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• 1996

Most real image sequences contain multiple moving objects or multiple motions. In this paper, we segmented the moving objects with optical flow. Motion estimation by this method can estimate and compress the image sequences better than other methods such as block matching method. And, especially, we can make new image sequences by synthesizing the segmented objects. But, it takes too much time for motion estimation. And, it is not easy for a hardware implementation.

• Earthquakes and Structures
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• v.22 no.4
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• pp.373-386
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• 2022

The development of performance-based design methodologies requires a reasonable definition of a displacement-response spectrum. Although ground motions are known to be significantly affected by the resonant-like amplification behavior caused by multiple wave reflections within the surface soil, such a soil-resonance effect is seldom explicitly considered in current-displacement spectral models. In this study, an analytical approach is developed for the construction of displacement-response spectra by considering the soil-resonance effect. For this purpose, a simple and rational equation is proposed for the response spectral ratio at the site fundamental period (SRTg) to represent the soil-resonance effect based on wave multiple reflection theory. In addition, a bilinear model is adopted to construct the soil displacement-response spectra. The proposed model is verified by comparing its results with those obtained from actual observations and SHAKE analyses. The results show that the proposed model can lead to very good estimations of SRTg for harmonic incident seismic waves and lead to reasonable estimations of SRTg and soil displacement-response spectra for earthquakes with a relatively large magnitude, which are generally considered for seismic design, particularly in high-seismicity regions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.3
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• pp.700-712
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• 2011

Due to recently advanced electrical devices, human can access computer network regardless of working location or time restriction. However, currently widely used mouse, joystick, and trackball input system are not easy to carry and they bound user hands exclusively within working space. Those make user inconvenient in Ubiquitous environments.. In this paper, we propose multiple dimension human motion detection system based on wireless sensor networks. It is a portable input device and provides easy installation process and unbinds user hands during input processing stages. Our implemented system is comprised of three components. One is input unit that senses user motions and transmits collected data to receiver. Second is receiver that conveys the received data to application, which runs on server computer. Third is application that performs command operations according to received data. Experiments shows that proposed system accurately detect the characteristics of user arm motions and fully support corresponding input requests.