• 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.

• The Korean Journal of Financial Management
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• v.20 no.1
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• pp.125-162
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• 2003

This paper investigates the short- and long- run relationship among Korean, U.S. and Japanese construction indices. We conducted the Johansen's cointegration tests on the hypotheses that the construction indices of three countries we related in the long-run as well as in the short-run. The test results show that there exists no long-run relationship among three countrie's construction indices. In addition, the cointegrating relation did not exist for three countrie's stock market indices and five major Korean construction firms. It fumed out that the U.S. indices Granger-causes Japanese and Korean indices. This finding implies that there may exist international diversification benefit through forming a portfolio from these indices.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.4
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• pp.101-112
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• 1985

It is important to extract the mechanical informations from the image sequences of the moving object. We have studied the computer algorithms for analysis of the moving heart using X-ray image sequence. A new mathematical method was developed to estimate the local epicardial deformation, wall thickness, and the regional circumferential and longitudinal wall stress using biplane coronary cineangiograms. In this method, the motion images of the coronary artery bifurca-tion points were used as natural landmarks for the kinematic analysis of the ventricular deformation. In four dogs and a normal patient's coronary cineangiograms, the estimation results show the validity of the present analysis, compared with the experimental results based upon the implanted markers. Thus, the present method provides a new method of evaluating the regional wall deformation and wall stress together with the blood vessel conditions using the coronary cineangiography procedure.

• Journal of Advanced Navigation Technology
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• v.22 no.3
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• pp.220-227
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• 2018

The most widely used method for constructing an inertial navigation system (INS)/global navigation satellite system (GNSS) coupling system is to construct an integrated navigation system using a Kalman filter. However, depending on the trajectory, non-observable state variables may be generated. In this case, the state variables are not estimated. To solve this problem, a integrated navigation system is constructed and then an observability analysis is performed. In this paper, a 24th order position-matched Kalman filter is defined to design an INS/GNSS integrated navigation system for vehicles moving with a large pitch angle change. To verify the appropriateness of the error state variables applied to the Kalman filter, an observability analysis was performed. The trajectory was divided into five segments, and the piece-wise constant system (PWCS) was assumed for each segment, and the results were analytically analyzed. The analytical results and the simulation results confirm that the error state parameters of the Kalman filter are well-designed to the estimation side.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.301-312
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• 2015

The purpose of this paper is to establish the epidemic model to explain the process of disease spread. The process of disease spread can be classified into two types: deterministic process and stochastic process. Most studies supposed that the process follows the deterministic process and established the model using the ordinary differential equation. In this article, we try to build the disease spread prediction model based on the SIR (Suspectible - Infectious - Recovered) model. we first estimated the model parameters using least squared method and applied to a deterministic model using ordinary differential equation. we also applied to a stochastic model based on Gillespie algorithm. The methods introduced in this paper are applied to the data on the number of cases of malaria every week from January 2001 to March 2003, released by Korea Centers for Disease Control and Prevention. As a result, we conclude that our model explains well the process of disease spread.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.36-42
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• 2009

In the mobile device environment, the context-aware computing has been emerging as a core technology of ubiquitous computing. Compared with a desktop computer, a user interface and resource of mobile device is very limited. Traditional desktop-based user interface has been developed on the basis that a user's activity is static state. In contrast, mobile devices are not able to utilize representative desktop-based interaction mechanisms such as a keyboard and mouse, not only because the activity of a user is dynamic state, but mobile devices have limited resources and small LCD display. In this paper, we introduce an intelligent control system for the mobile device that can utility effectively the limited resource and complement the poor user interface by using an accelerometer being able to sense the physical activity and posture. The proposed system can estimate the user activity, static and dynamic states, and posture watching the PDA at the same time, and the proposed intelligent control system as its application, the backlight ON/OFF on the PDA, is run by the result of the user's behavior.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.4
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• pp.86-93
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• 2011

The ship movement implies current position, wave, wind, and its other factors. We need to know exactly the location and the shape of the ship and control its motion because of these effects. In order to control the small ship according to the movement of the large ship, the position and shape of the ship should be given first. In this paper we propose the method with which we know the current status of the ship without dynamic equations of the ship. There are several methods to track the system such as optical, radio frequency, radar, camera, and infrared light. We propose the movement of the ship using the GPS absolute axis. But, the genuine error by the GPS itself and the movement of the ship cause the result of the GPS of not being accurate. This paper reduces the error of the location and the shape of the ship and gives the exact values of the ship movements even if the GPS implies some error itself.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.133-141
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• 2008

As interactive multimedia have come into wide use, user interfaces such as remote controllers or classical computer mice have several limitations that cause inconvenience. We propose a vision-based pointing device to resolve this problem. We analyzed the moving image from the camera which is embedded in the pointing device and estimate the movement of the device. The pose of the cursor can be determined from this result. To process in the real time, we used the low resolution of $288{\times}208$ pixel camera and comer points of the screen were tracked using local optical flow method. The distance from screen and device was calculated from the size of screen in the image. The proposed device has simple configurations, low cost, easy use, and intuitive handhold operation like traditional mice. Moreover it shows reliable performance even in the dark condition.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.85-95
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• 2019

This work shows how to design a robot structure and to control to overcome obstacles while traveling through ducts of various diameters and shapes by three-legged robot. Circuits are centered in the body to connect the three wheel bodies that are driven around the center body with the 4-section slider link structure. Also, the springs are used to contract and expand the robot legs so that it can be caparable of various environments. Geared motor, spring, and belt were selected based on the static and dynamic calculation to be suitable to horizontal and vertical travels. The center body is equipped with a camera and the distance sensors, and a control algorithms are implemented so that it can be successfully performed in L-type and T-type ducts. Using UWB modules and trilateration algorithm, the location of the duct-cleaning robot inside the duct could be identified successfully.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.85-92
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• 2017

Recently, in the field of video surveillance, a Deep Learning based learning method has been applied to a method of detecting a moving person in a video and analyzing the behavior of a detected person. The human activity recognition, which is one of the fields this intelligent image analysis technology, detects the object and goes through the process of detecting the body keypoint to recognize the behavior of the detected object. In this paper, we propose a method for Body Keypoint Localization based on Object Detection using RGB-D information. First, the moving object is segmented and detected from the background using color information and depth information generated by the two cameras. The input image generated by rescaling the detected object region using RGB-D information is applied to Convolutional Pose Machines for one person's pose estimation. CPM are used to generate Belief Maps for 14 body parts per person and to detect body keypoints based on Belief Maps. This method provides an accurate region for objects to detect keypoints an can be extended from single Body Keypoint Localization to multiple Body Keypoint Localization through the integration of individual Body Keypoint Localization. In the future, it is possible to generate a model for human pose estimation using the detected keypoints and contribute to the field of human activity recognition.