• Journal of Astronomy and Space Sciences
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• 제36권3호
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• pp.169-180
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• 2019

In this study, a batch least square estimator that utilizes optical observation data is developed and utilized to determine geostationary orbits (GEO). Through numerical simulations, the effects of error sources, such as clock errors, measurement noise, and the a priori state error, are analyzed. The actual optical tracking data of a GEO satellite, the Communication, Ocean and Meteorological Satellite (COMS), provided by the optical wide-field patrol network (OWL-Net) is used with the developed batch filter for orbit determination. The accuracy of the determined orbit is evaluated by comparison with two-line elements (TLE) and confirmed as proper for the continuous monitoring of GEO objects. Also, the measurement residuals are converged to several arcseconds, corresponding to the OWL-Net performance. Based on these analyses, it is verified that the independent operation of electro-optic space surveillance systems is possible, and the ephemerides of space objects can be obtained.

• 한국통신학회논문지
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• 제39C권8호
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• pp.731-737
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• 2014

본 논문에서는 감시 카메라 환경에서 발생할 수 있는 군중의 비정상 행동 검출 방법을 제안한다. 군중들의 비정상 행동을 산발적으로 퍼지면서 뛰는 행동, 한쪽 방향으로 갑자기 뛰는 행동 두 가지로 정의하였다. 이를 검출하기 위하여 영상에서 움직임 벡터를 추출하여 군중의 비정상 행동 검출에 적합한 서술자 MHOF(Multi-scale Histogram of Optical Flow)와 DCHOF(Directional Change Histogram of Optical Flow)제안하였으며, 이를 이진 분류기인 SVM(Support Vector Machine)을 이용하여 검출하였다. 제안한 방법은 공개 데이터셋인 UMN 데이터와 PETS 2009 데이터를 이용하여 성능을 평가하였고 다른 방법론과의 비교를 통해 제안하는 알고리즘의 우수성을 입증하였다.

• Journal of Astronomy and Space Sciences
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• 제36권3호
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• pp.187-197
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• 2019

The Optical Wide-field patroL-Network (OWL-Net) is a Korean optical space surveillance system used to track and monitor objects in space. In this study, the characteristics of four Initial Orbit Determination (IOD) methods were analyzed using artificial observational data from Low Earth Orbit satellites, and an appropriate IOD method was selected for use as the initial value of Precise Orbit Determination using OWL-Net data. Various simulations were performed according to the properties of observational data, such as noise level and observational time interval, to confirm the characteristics of the IOD methods. The IOD results produced via the OWL-Net observational data were then compared with Two Line Elements data to verify the accuracy of each IOD method. This paper, thus, suggests the best method for IOD, according to the properties of angles-only data, for use even when the ephemeris of a satellite is unknown.

• Journal of Astronomy and Space Sciences
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• 제28권4호
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• pp.319-332
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• 2011

The objectives of this study are to analyze the satellite visibility at the randomly established ground sites, to determine the five optimal ground sites to perform the optical surveillance and tracking of domestic satellites, and to verify the acquisition of the optical observation time sufficient to maintain the precise ephemeris at optimal ground sites that have been already determined. In order to accomplish these objectives, we analyzed the visibility for sun-synchronous orbit satellites, low earth orbit satellites, middle earth orbit satellites and domestic satellites as well as the continuous visibility along with the fictitious satellite ground track, and calculate the effective visibility. For the analysis, we carried out a series of repetitive process using the satellite tool kit simulation software developed by Analytical Graphics Incorporated. The lighting states of the penumbra and direct sun were set as the key constraints of the optical observation. The minimum of the observation satellite elevation angle was set to be 20 degree, whereas the maximum of the sun elevation angle was set to be -10 degree which is within the range of the nautical twilight. To select the candidates for the optimal optical observation, the entire globe was divided into 84 sectors in a constant interval, the visibility characteristics of the individual sectors were analyzed, and 17 ground sites were arbitrarily selected and analyzed further. Finally, five optimal ground sites (Khurel Togoot Observatory, Assy-Turgen Observatory, Tubitak National Observatory, Bisdee Tier Optical Astronomy Observatory, and South Africa Astronomical Observatory) were determined. The total observation period was decided as one year. To examine the seasonal variation, the simulation was performed for the period of three days or less with respect to spring, summer, fall and winter. In conclusion, we decided the optimal ground sites to perform the optical surveillance and tracking of domestic satellites and verified that optical observation time sufficient to maintain the precise ephemeris could be acquired at the determined observatories.

• 한국멀티미디어학회논문지
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• 제21권8호
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• pp.829-836
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• 2018

This study attempts to detect a shot boundary in films(or dramas) based on the length of a sequence. As films or dramas use scene change effects a lot, the issues regarding the effects are more diverse than those used in surveillance cameras, sports videos, medical care and security. Visual techniques used in films are focused on the human sense of aesthetic therefore, it is difficult to solve the errors in shot boundary detection with the method employed in surveillance cameras. In order to define the errors arisen from the scene change effects between the images and resolve those issues, the mixed algorithm based upon color histogram, edge histogram, and optical flow was implemented. The shot boundary data from this study will be used when analysing the configuration of meaningful shots in sequences in the future.

• Journal of Astronomy and Space Sciences
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• 제34권1호
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• pp.19-30
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• 2017

The optical wide-field patrol network (OWL-Net) is a Korean optical surveillance system that tracks and monitors domestic satellites. In this study, a batch least squares algorithm was developed for optical measurements and verified by Monte Carlo simulation and covariance analysis. Potential error sources of OWL-Net, such as noise, bias, and clock errors, were analyzed. There is a linear relation between the estimation accuracy and the noise level, and the accuracy significantly depends on the declination bias. In addition, the time-tagging error significantly degrades the observation accuracy, while the time-synchronization offset corresponds to the orbital motion. The Cartesian state vector and measurement bias were determined using the OWL-Net tracking data of the KOMPSAT-1 and Cryosat-2 satellites. The comparison with known orbital information based on two-line elements (TLE) and the consolidated prediction format (CPF) shows that the orbit determination accuracy is similar to that of TLE. Furthermore, the precision and accuracy of OWL-Net observation data were determined to be tens of arcsec and sub-degree level, respectively.

• Journal of Astronomy and Space Sciences
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• 제28권3호
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• pp.193-201
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• 2011

A strategy for geostationary orbit (or geostationary earth orbit [GEO]) surveillance based on optical angular observations is presented in this study. For the dynamic model, precise analytical orbit model developed by Lee et al. (1997) is used to improve computation performance and the unscented Kalman filer (UKF) is applied as a real-time filtering method. The UKF is known to perform well under highly nonlinear conditions such as surveillance in this study. The strategy that combines the analytical orbit propagation model and the UKF is tested for various conditions like different level of initial error and different level of measurement noise. The dependencies on observation interval and number of ground station are also tested. The test results shows that the GEO orbit determination based on the UKF and the analytical orbit model can be applied to GEO orbit tracking and surveillance effectively.

• 한국인터넷방송통신학회논문지
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• 제12권2호
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• pp.103-110
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• 2012

수동적인 보안감시 시스템의 문제점이 계속적으로 제기되면서 실시간으로 공공장소에서의 군중에 대한 관리 및 감독을 지원하는 자동화되고 지능적인 군중 밀도 측정에 대한 필요성이 증대되고 있다. 이에 따라, 군중의 밀도를 측정하기 위한 많은 연구가 시도되었으나 실시간 혼잡도 정보 취득이 어렵고, 조명변화 등에 취약한 한계가 드러났다. 본 논문에서는 이러한 문제점을 해결하기 위해 군중 특징 정보로써 옵티컬 플로우를 검출하고 또한 Sobel 외곽선 추출 알고리즘에 의해 외곽선을 추출하여 각 특징을 입력으로 학습된 다층 신경망을 통해 실시간으로 실외 공공장소에서의 군중 밀도를 측정하였다.

• 한국광학회:학술대회논문집
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• 한국광학회 2005년도 하계학술발표회
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• pp.36-37
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• 2005

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.2948-2963
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• 2015

In the field of computer vision, visual surveillance systems have recently become an important research topic. Growth in this area is being driven by both the increase in the availability of inexpensive computing devices and image sensors as well as the general inefficiency of manual surveillance and monitoring. In particular, the ultimate goal for many visual surveillance systems is to provide automatic activity recognition for events at a given site. A higher level of understanding of these activities requires certain lower-level computer vision tasks to be performed. So in this paper, we propose an intelligent activity recognition model that uses a structure learning method and a classification method. The structure learning method is provided as a K2-learning algorithm that generates Bayesian networks of causal relationships between sensors for a given activity. The statistical characteristics of the sensor values and the topological characteristics of the generated graphs are learned for each activity, and then a neural network is designed to classify the current activity according to the features extracted from the multiple sensor values that have been collected. Finally, the proposed method is implemented and tested by using PETS2013 benchmark data.