• Proceedings of the Korean Society of Marine Engineers Conference
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• 2001.05a
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• pp.219-224
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• 2001

This paper presents the development of a tracking algorithm for shipboard satellite antenna systems which can enhance the tracking performance. In order to overcome some drawbacks of the conventional step tracking algorithm, the proposed algorithm searches for the best tracking angles using gradient-based formulae and signal intensities measured according to a search pattern. The effectiveness of the proposed algorithm is demonstrated through simulation using real-world data.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.1 s.232
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• pp.139-144
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• 2005

A vehicle cruise control algorithm using an Interacting Multiple Model (IMM)-based Multi-Target Tracking (MTT) method has been presented in this paper. The vehicle cruise control algorithm consists of three parts; track estimator using IMM-Probabilistic Data Association Filter (PDAF), a primary target vehicle determination algorithm and a single-target adaptive cruise control algorithm. Three motion models; uniform motion, lane-change motion and acceleration motion. have been adopted to distinguish large lateral motions from longitudinal motions. The models have been validated using simulated and experimental data. The improvement in the state estimation performance when using three models is verified in target tracking simulations. The performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. These simulations show system response that is more realistic and reflective of actual human driving behavior.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.108-114
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• 2022

Autism (ASD) is a mental disorder characterized by a pronounced deficit in personal, social, speech, and other aspects of development and communication skills. Since autism is a complex developmental disorder that requires a lot of effort to recognize, this research was conducted to develop an interactive data Acquisition System and detect the first signs of ASD in children. The proposed system presents several variants of the tasks in an entertaining form, using hand tracking. Hand tracking is used to attract children's attention and interest them more to achieve more accurate results. The creation of the system is based on such libraries as OpenCV, PyGame, TensorFlow, and Mediapipe. The ultimate goal of the paper is to obtain data on the disease of autism in children for use in further diagnosis by medical experts.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.359-373
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• 2022

The new crown pneumonia (COVID-19) has become a global epidemic. The disease has spread to most countries and poses a challenge to the healthcare system. Contact tracing technology is an effective way for public health to deal with diseases. Many experts have studied traditional contact tracing and developed digital contact tracking. In order to better understand the field of contact tracking, it is necessary to analyze the development of contact tracking in the field of computer science by bibliometrics. The purpose of this research is to use literature statistics and topic analysis to characterize the research literature of contact tracking in the field of computer science, to gain an in-depth understanding of the literature development status of contact tracking and the trend of hot topics over the past decade. In order to achieve the aforementioned goals, we conducted a bibliometric study in this paper. The study uses data collected from the Scopus database. Which contains more than 10,000 articles, including more than 2,000 in the field of computer science. For popular trends, we use VOSviewer for visual analysis. The number of contact tracking documents published annually in the computer field is increasing. At present, there are 200 to 300 papers published in the field of computer science each year, and the number of uncited papers is relatively small. Through the visual analysis of the paper, we found that the hot topic of contact tracking has changed from the past "mathematical model," "biological model," and "algorithm" to the current "digital contact tracking," "privacy," and "mobile application" and other topics. Contact tracking is currently a hot research topic. By selecting the most cited papers, we can display high-quality literature in contact tracking and characterize the development trend of the entire field through topic analysis. This is useful for students and researchers new to field of contact tracking ai well as for presenting our results to other subjects. Especially when comprehensive research cannot be conducted due to time constraints or lack of precise research questions, our research analysis can provide value for it.

• Journal of Korea Society of Digital Industry and Information Management
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• v.20 no.3
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• pp.13-23
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• 2024

For the purpose of predicting credit card customer churn accurately through data analysis Detecting and tracking objects in continuous video is essential in self-driving cars, security and surveillance systems, sports analytics, medical image processing, and more. Correlation tracking methods such as Normalized Cross Correlation(NCC) and Sum of Absolute Differences(SAD) are used as an effective way to measure the similarity between two images. NCC, a representative correlation tracking method, has been useful in real-time environments because it is relatively simple to compute and effective. However, correlation tracking methods are sensitive to rotation and size changes of objects, making them difficult to apply to real-time changing videos. To overcome these limitations, this paper proposes an object tracking method using the Histogram of Oriented Gradients(HOG) feature to effectively obtain object data and the Convolution Neural Network(CNN) algorithm. By using the two algorithms, the shape and structure of the object can be effectively represented and learned, resulting in more reliable and accurate object tracking. In this paper, the performance of the proposed method is verified through experiments and its superiority is demonstrated.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.11
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• pp.1016-1027
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• 2015

In this paper, a orbit determination process was carried out based on KARISMA(KARI Collision Risk Management System) developed by KARI(Korea Aerospace Research Institute) to verify the orbit determination performance of this system, in which radar tracking data of a space debris was used. The real radar tracking data were obtained from TIRA(Tracking & Imaging Radar) system operated by GSOC(German Space Operation Center) for the KITSAT-3 finished satellite. And orbit determination error was approximately 60m compared to that of the GSOC's orbit determination result from the same radar tracking data. However, those results were influenced due to the insufficient information on the radar tracking data, such as error correction. To verify and confirm it, the error analysis was demonstrated and first observation data arc which has huge observation error was rejected. In this result, the orbit determination error was reduced such as approximately 25m. Therefore, if there are some observation data information such as error correction data, it is expected to improve the orbit determination accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2335-2340
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• 2009

This paper presents how to implement Markerless Augmented Reality and how to create and apply reference data sets. There are three parts related with implementation: setting camera, creation of reference data set, and tracking. To create effective reference data sets, we need a 3D model such as CAD model. It is also required to create reference data sets from various viewpoints. We extract the feature points from the mode1 image and then extract 3D positions corresponding to the feature points using ray tracking. These 2D/3D correspondence point sets constitute a reference data set of the model. Reference data sets are constructed for various viewpoints of the model. Fast tracking can be done using a reference data set the most frequently matched with feature points of the present frame and model data near the reference data set.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.8
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• pp.661-673
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• 2014

In this paper, a precise orbit determination process was carried out based on KARISMA(KARI Collision Risk Management System) developed by KARI(Korea Aerospace Research Institute), in which optical tracking data of a geostationary satellite was used. The real optical tracking data provided by ESA(European Space Agency) for the ARTEMIS geostationary satellite was used. And orbit determination error was approximately 420 m compared to that of the ESA's orbit determination result from the same optical tracking data. In addition, orbit prediction was conducted based on the orbit determination result with optical tracking data for 4 days, and the position error for the orbit prediction during 3 days was approximately 500~600 m compared to that of ESA's result. These results imply that the performance of the KARISMA's orbit determination function is suitable to apply to the collision risk assessment for the space debris.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2483-2503
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• 2016

Traffic congestion is a severe problem in many modern cities around the world. Real-time and accurate traffic congestion identification can provide the advanced traffic management systems with a reliable basis to take measurements. The most used data sources for traffic congestion are loop detector, GPS data, and video surveillance. Video based traffic monitoring systems have gained much attention due to their enormous advantages, such as low cost, flexibility to redesign the system and providing a rich information source for human understanding. In general, most existing video based systems for monitoring road traffic rely on stationary cameras and multiple vehicle tracking method. However, most commonly used multiple vehicle tracking methods are lack of effective track initiation schemes. Based on the motion of the vehicle usually obeys constant velocity model, a novel vehicle recognition method is proposed. The state of recognized vehicle is sent to the GM-PHD filter as birth target. In this way, we relieve the insensitive of GM-PHD filter for new entering vehicle. Combining with the advanced vehicle detection and data association techniques, this multiple vehicle tracking method is used to identify traffic congestion. It can be implemented in real-time with high accuracy and robustness. The advantages of our proposed method are validated on four real traffic data.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.4
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• pp.114-119
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• 2006

Data post-processing programs are used for analysis and visualization of the data obtained from computational fluid methods or flow field experiments. In this paper 3D data visualization system which combines a data visualization program with position tracking system using stereo cameras is introduced. This system offers virtual environment for visualization and analysis of three dimensional data.