• Journal of IKEEE
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• v.13 no.2
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• pp.232-240
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• 2009

This paper presents a robust vehicle detection and tracking algorithm for supervision of illegal parking. The proposed algorithm is composed of four parts. First, a vehicle detection algorithm is proposed using the improved codebook object detection algorithm to segment moving vehicles from the input sequence. Second, a preprocessing technique using the geometric characteristics of vehicles is employed to exclude non-vehicle objects. Then, the detected vehicles are tracked by an object tracker which incorporates histogram tracking method with Kalman filter. To make the tracking results more accurate, histogram tracking results are used as measurement data for Kalman filter. Finally, Real Stop Counter (RSC) is introduced for trustworthy and accurate performance of the stopped vehicle detection. Experimental results show that the proposed algorithm can track multiple vehicles simultaneously and detect stopped vehicles successfully in the complicated street environment.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.766-772
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• 2015

This paper proposes an object detection method based on motion estimation using background subtraction in the fisheye images obtained through omni-directional camera mounted on the vehicle. Recently, most of the vehicles installed with rear camera as a standard option, as well as various camera systems for safety. However, differently from the conventional object detection using the image obtained from the camera, the embedded system installed in the vehicle is difficult to apply a complicated algorithm because of its inherent low processing performance. In general, the embedded system needs system-dependent algorithm because it has lower processing performance than the computer. In this paper, the location of object is estimated from the information of object's motion obtained by applying a background subtraction method which compares the previous frames with the current ones. The real-time detection performance of the proposed method for object detection is verified experimentally on embedded board by comparing the proposed algorithm with the object detection based on LKOF (Lucas-Kanade optical flow).

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.12
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• pp.1115-1123
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• 2011

This paper proposes an image processing algorithms for detection and tracking of aerial vehicles in short-range. Proposed algorithm detects moving objects by using image homography calculated from consecutive video frames and determines whether the detected objects are approaching aerial vehicles by the Probabilistic Multi-Hypothesis Tracking method(PMHT). This algorithm can perform better than simple color-based detection methods since it can detect moving objects under complex background such as the ground seen during low altitude flight and consider the characteristics of vehicle dynamics. Furthermore, it is effective for the flight test due to the reduction of thresholding sensitivity against external factors. The performance of proposed algorithm is verified by applying to the onboard video obtained by flight test.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.2
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• pp.170-178
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• 2017

This paper proposes an improved path-planning technique based on the $A^*$ algorithm. The conventional $A^*$ algorithm only considers the optimality of the planned path and sometimes produces a path that an unmanned underwater vehicle (UUV) cannot navigate due to its dynamic constraint such as the limit of the radius of gyration. It is because that the previous method evaluate the moving cost based on the straight distance between nodes. We enhance the conventional method by evaluating the moving cost on the basis of the practically navigable trajectory, which is generated by the waypoint-tracking control of the UUV dynamics. The simulation examples indeed show the effectiveness of the proposed technique.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.93-101
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• 2023

In this paper, we propose a method of creating a 3D bounding box for an object using a vanishing point to increase the accuracy of object recognition in an image when recognizing an traffic object using a video camera. Recently, when vehicles captured by a traffic video camera is to be detected using artificial intelligence, this 3D bounding box generation algorithm is applied. The vertical vanishing point (VP1) and horizontal vanishing point (VP2) are derived by analyzing the camera installation angle and the direction of the image captured by the camera, and based on this, the moving object in the video subject to analysis is specified. If this algorithm is applied, it is easy to detect object information such as the location, type, and size of the detected object, and when applied to a moving type such as a car, it is tracked to determine the location, coordinates, movement speed, and direction of each object by tracking it. Able to know. As a result of application to actual roads, tracking improved by 10%, in particular, the recognition rate and tracking of shaded areas (extremely small vehicle parts hidden by large cars) improved by 100%, and traffic data analysis accuracy was improved.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.10
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• pp.52-60
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• 2010

It is generally important to get a precise position information for autonomous unmanned vehicle(AUV) to run safely. For getting the position of AUV, the GPS has been using to navigation in a vehicle. Though it is useful to finding a position, it is difficult to precisely control a trajectory of the AUV due to large measuring error which may reach over 10 meters. Therefore to apply AUV it needs to compensate for the error. This paper proposes a method to more precisely localize AUV using three low-cost differential global positioning systems (DGPS). The distance errors between each DGPS are minimized as using the least square method (LSM) and the Kalman filter to eliminate a Gaussian white noise. The selected DGPS is cheaper and easier to set up than the RTK-GPS. It is also more precise than the general GPS. The proposed method can compensate the relatively position error according to stationary and moving distance of the AUV. For evaluating the algorithm by simulation, the DGPS signal with the Gaussian white noise to any points is generated by the AR model and compared with the measurement signal. It is confirmed that the proposed method can effectively compensate the position error as comparing with the measurement signal. The compensated position signal can be used to localize and control the AUV in the road.

• Journal of the Korea Society for Simulation
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• v.24 no.4
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• pp.163-170
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• 2015

This research is to focus on the method of moving line optimization in Agricultural Industry, especially Garak Wholesale Market Modernization Project, by using simulation tool. As everybody knew, it's very difficult to apply the SCM operation rules in Agricultural Industry, because the standardization system in Agricultural Industry was not completed. The five flow management factors, vehicle moving line management, customer moving line Management, Logistics Device Moving Line Management, Working Person Moving Line Management, Product display moving line management, are needed to be optimized on the basis of standardization rules, and to achieve this will be the good infrastructure to make the Agricultural SCM system. It's very different between the SCM structure of manufacturing industry and logistics industry and the SCM structure of Agricultural Industry, because the SCM in manufacturing is occur in the basis of flow management, on the contrary, the SCM of Agricultural Industry is on the basis of activity management. For these reason, this study is the first approach to apply the simulation method in the part of moving line optimization in Agricultural SCM, and in near future, This study will help all designers and operators to apply the simulation work in the part of agricultural SCM, and we hope that next advanced study will continue by using this study.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.2
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• pp.143-148
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• 2014

Particle filter algorithm has been proven very successful for non-linear and non-Gaussian estimation problem and thus it has been widely used for object tracking for video signals. If the object moves significantly, particle filter needs very large number of particles to track object and this results high computational cost. In this paper, modified particle filter by adopting motion vector is proposed for tracking vehicle in low frame rate(LPR) video input, which the object moving significantly and randomly between consecutive frames. In the proposed algorithm, motion vector is applied in selection and observe step. The experimental result shows that the proposed particle filter can track vehicle successfully in the case when previous one fails. And it also shows the propose method increases the precision of tracking.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.679-685
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• 2001

In this paper, the dynamic response of the pantograph system that supplies electrical power to a high-speed rail vehicle were investigated. The analysis of the catenary based on the Finite Element Method (FEM) is executed to develop a pantograph fits well in high-speed focused on the dynamic characteristic analysis of the pantograph system. By simulation of the pantograph-catenary system, the static deflection of the catenary, the stiffness variation in contact lines, the dynamic response of the catenary undergoing constant moving load and the contact force analysis were executed. In order to consider the design variables that effects on the dynamic characteristic of the pantograph system performed the dynamic sensitivity analysis. From the pantograph-catenary analysis, the design parameters of a pantograph could be improved. From the results of the sensitivity analysis, a pantograph with improved parameters is suitable for a high-speed rail vehicle from the design-parameter analysis.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.8
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• pp.783-789
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• 2007

In this paper, firstly, we propose a generating method of the 3-D obstacle map using ultrasonic sensors. Secondly, we try to find the necessary stimulation conditions of compact tactile display device for effective transfer of obstacle information. The final goal of this research is the development of a walking guide system for the blind to walk safely. The walking guide system consists of a guide vehicle for the obstacle detection and a tactile display device for the transfer of the obstacle information. The guide vehicle, located in front of the walking blind, detects the obstacle using ultrasonic sensors. The processed information makes an obstacle map and transmits safe path and emergency situation to the blind by the tactile display. The tactile display device, located in the handle which is connected with the guide vehicle by cane, offers the processed obstacle information such as position, size, moving, shape of obstacle and safe path, etc. The concept of a walking guide system with tactile display is introduced, and experiments of 3-D obstacle detection and tactile perception are carried out and analyzed.