• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.1
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• pp.1-11
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• 2014

In this paper we propose a system for vehicle detection and tracking which has the ability to learn on-line appearance changes of vehicles being tracked. The proposed system uses feature-based tracking method to estimate rapidly and robustly the motion of the newly detected vehicles between consecutive frames. Simultaneously, the system trains an online vehicle detector for the tracked vehicles. If the tracker fails, it is re-initialized by the detection of the online vehicle detector. An improved vehicle appearance model update rule is presented to increase a tracking performance and a speed of the proposed system. Performance of the proposed system is evaluated on the dataset acquired on various driving environment. In particular, the experimental results proved that the performance of the vehicle tracking is significantly improved under bad conditions such as entering a tunnel and passing rain.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.2
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• pp.217-226
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• 2006

Extraction and tracking objects are fundamental and important steps of the digital image processing and computer vision. Many algorithms about extracting and tracking objects have been developed. In this research, a method is suggested for tracking a moving object using a pair of CCD cameras and calculating the coordinate of the moving object. A 1/100 miniature of soccer field was made to apply the developed algorithms. After candidates were selected from the acquired images using the RGB value of a moving object (soccer ball), the object was extracted using its size (MBR size) among the candidates. And then, image coordinates of a moving object are obtained. The real-time position of a moving object is tracked in the boundary of the expected motion, which is determined by centering the moving object. The 3D position of a moving object can be obtained by conducting the relative orientation, absolute orientation, and space intersection of a pair of the CCD camera image.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.250-256
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• 2009

This paper presents a robotic tower-crane system using encoder and gyroscope sensors as path tracking devices. Tower crane work is often associated with falling accidents and industrial disasters. Such problems often incur a loss of time and money for the contractor. For this reason, many studies have been done on an automatic tower crane. As a part of 5-year 23-million-dollar research project in Korea, we are developing a robotic tower crane which aims to improve the safety level and productivity. We selected a luffing tower crane, which is commonly used in urban construction projects today, as a platform for the robotic tower crane system. This system comprises two modules: the automated path planning module and the path tracking module. The automated path planning system uses the 3D Cartesian coordinates. When the robotic tower crane lifts construction material, the algorithm creates a line, which represents a lifting path, in virtual space. This algorithm seeks and generates the best route to lift construction material while avoiding known obstacles from real construction site. The path tracking system detects the location of a lifted material in terms of the 3D coordinate values using various types of sensors including adopts encoder and gyroscope sensors. We are testing various sensors as a candidate for the path tracking device. This specific study focuses on how to employ encoder and gyroscope sensors in the robotic crane These sensors measure a movement and rotary motion of the robotic tower crane. Finally, the movement of the robotic tower crane is displayed in a virtual space that synthesizes the data from two modules: the automatically planned path and the tracked paths. We are currently field-testing the feasibility of the proposed system using an actual tower crane. In the next step, the robotic tower crane will be applied to actual construction sites with a following analysis of the crane's productivity in order to ascertain its economic efficiency.

• The KIPS Transactions:PartD
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• v.13D no.2 s.105
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• pp.175-182
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• 2006

Radars are used to detect the motion of the low flying enemy planes in the military. Radar-detected raw data are first processed and then inserted into the ground tactical C4I system. Next, these data we analyzed and broadcasted to the Shooter system in real time. But the accuracy of information and time spent on the displaying and graphical computation are dependent on the operator's capability. In this paper, we propose the Flying Object Tracking Management System that allows the displaying of the objects' trails in real time by using data received from the radars. We apply the coordinate system translation algorithm, existing communication protocol improvements with communication equipment, and signal and information computation process. Especially, radar signal duplication computation and synchronization algorithm is developed to display the objects' coordinates and thus we can improve the Tactical Air control system's reliability, efficiency, and easy-of-usage.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.420-426
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• 1998

It is the purpose of this paper to make a preliminary study on the use of repetitive control to improve velocity accuracy by eliminating repetitive disturbances caused by machining inaccuracies of the axis of rotation location. If the control system can be intelligent enough to compensate for such machining errors, then one may be able to improve the accuracy of the velocity control, or alternatively, one may maintain the same accuracy and relax the machining tolerances required. This could decrease cost significantly. Experiments are performed testing repetitive control methods on a constant speed rolling operation testbed. The experimental results show very substantial decreases in the tracking error of the system. Spectral data of the output motion are given to demonstrate the attenuation of the disturbance frequencies and harmonics, related to the bandwidth being used. It is seen that the simplest form of repetitive control which is very easily implemented, can produce striking improvement in control system performance in such belt drive rolling operations, and the learning can be accomplished in a short time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.3
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• pp.568-576
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• 2003

This paper proposes a moving object tracking algorithm by using hierarchical search method in dynamic scenes. Proposed algorithm is based on two main steps: generation step of initial model from different pictures, and tracking step of moving object under the time-yawing scenes. With a series of this procedure, tracking process is not only stable under far distance circumstance with respect to the previous frame but also reliable under shape variation from the 3-dimensional(3D) motion and camera sway, and consequently, by correcting position of moving object, tracking time is relatively reduced. Partial Hausdorff distance is also utilized as an estimation function to determine the similarity between model and moving object. In order to testify the performance of proposed method, the extraction and tracking performance have tested using some kinds of moving car in dynamic scenes. Experimental results showed that the proposed algorithm provides higher performance. Namely, matching order is 28.21 times on average, and considering the processing time per frame, it is 53.21ms/frame. Computation result between the tracking position and that of currently real with respect to the root-mean-square(rms) is 1.148. In the occasion of different vehicle in terms of size, color and shape, tracking performance is 98.66%. In such case as background-dependence due to the analogy to road is 95.33%, and total average is 97%.

• Journal of Advanced Navigation Technology
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• v.9 no.1
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• pp.48-55
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• 2005

In this paper, we propose an efficient moving object tracking technique for multi-camera surveillance system. Color CCD cameras used in this system are network cameras with their own IP addresses. Input image is transmitted to the media server through wireless connection among server, bridge, and Access Point (AP). The tracking system sends the received images through the network to the tracking module, and it tracks moving objects in real-time using color matching method. We compose two sets of cameras, and when the object is out of field of view (FOV), we accomplish hand-over to be able to continue tracking the object. When hand-over is performed, we use MHI(Motion History Information) based on color information and M-bin histogram for an exact tracking. By utilizing MHI, we can calculate direction and velocity of the object, and those information helps to predict next location of the object. Therefore, we obtain a better result in speed and stability than using template matching based on only M-bin histogram, and we verified this result by an experiment.

• Journal of the Korea Computer Graphics Society
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• v.24 no.3
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• pp.73-81
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• 2018

In this paper, we present a motion-driven rowing simulation framework that allows multiple players to row a boat together by their harmonized movements. In the actual rowing game, it is crucial for the players to synchronize their rowing with respect to time and pose so as to accelerate the boat. Inspired by this interesting feature, we measure the motion similarity among multiple players in real time while they are doing rowing motions and use it to control the velocity of the boat in a virtual environment. We also employ game components such as catching an item which can accelerate or decelerate the boat depending on its type for a moment once it has been obtained by synchronized catching behaviors of the players. By these components, the players can be encouraged to more actively participate in the training for a good teamwork to produce harmonized rowing movements Our methods for the motion recognition for rowing and item catch require the tracking data only for the head and the both hands and are fast enough to facilitate the real-time performance. In order to enhance immersiveness of the virtual environment, we project the rowing simulation result on a wide curved screen.

• Smart Structures and Systems
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• v.18 no.5
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• pp.955-982
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• 2016

Recent studies integrating vibration control and structural health monitoring (SHM) use control devices and control algorithms to enable system identification and damage detection. In this study real-time SHM is used to enhance structural vibration control and reduce damage. A newly proposed control algorithm, including integrated real-time SHM and semi-active control strategy, is presented to mitigate both damage and seismic response of the main structure under strong seismic ground motion. The semi-active independently variable stiffness (SAIVS) device is used as semi-active control device in this investigation. The proper stiffness of SAIVS device is obtained using a new developed semi-active control algorithm based on real-time damage tracking of structure by damage detection algorithm based on identified system Markov parameters (DDA/ISMP) method. A three bay five story steel braced frame structure, which is equipped with one SAIVS device at each story, is employed to illustrate the efficiency of the proposed algorithm. The obtained results show that the proposed control algorithm could significantly decrease damage in most parts of the structure. Also, the dynamic response of the structure is effectively reduced by using the proposed control algorithm during four strong earthquakes. In comparison to passive on and off cases, the results demonstrate that the performance of the proposed control algorithm in decreasing both damage and dynamic responses of structure is significantly enhanced than the passive cases. Furthermore, from the energy consumption point of view the maximum and the cumulative control force in the proposed control algorithm is less than the passive-on case, considerably.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.1
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• pp.78-87
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• 1989

In this paper, a spatio-temporal gradient (STG) method with generalized least square estimation (GLSE) is proposed for the detection of an object motion in an image sequence corrupted by white Gaussian noise. The proposed method is applied to an automatic target tracker using a high speed 16-bit microprocessor in order to track one moving target in real time. Experimental results show that the proposed method has much better performance over the conventional one with least square estimation (LSE).