• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4355-4374
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• 2018

Crowd escape event detection has become one of the hottest problems in intelligent surveillance filed. When the 'escape event' occurs, pedestrians will escape in a disordered way with different velocities and directions. Based on these characteristics, this paper proposes a Direction-Collectiveness Model to detect escape event in crowd scenes. First, we extract a set of trajectories from video sequences by using generalized Kanade-Lucas-Tomasi key point tracker (gKLT). Second, a Direction-Collectiveness Model is built based on the randomness of velocity and orientation calculated from the trajectories to express the movement of the crowd. This model can describe the movement of the crowd adequately. To obtain a generalized crowd escape event detector, we adopt an adaptive threshold according to the Direction-Collectiveness index. Experiments conducted on two widely used datasets demonstrate that the proposed model can detect the escape events more effectively from dense crowd.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.2
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• pp.119-127
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• 2010

In this paper, we propose a new automatic surveillance tracking system that can extract the target from the complex background and foreground noises by using the image-based SAD algorithm and control the servo motor of cameras by using kanatani algorithm. From the experimental results the proposed stereo tracking system is found to track the target adaptively under the circumstance of complex and changing background noises and the possibility of real-time implementation of the proposed system by using the optical system is also suggested.

• Journal of Astronomy and Space Sciences
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• v.36 no.3
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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 Veterinary Clinics
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• v.30 no.4
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• pp.258-263
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• 2013

The primary goal of this study was to compute sample sizes required to achieve the each aim of a variety of foot-and-mouth disease (FMD) surveillance programs, using a statistically valid technique that takes the following factors into account: sensitivity (Se) and specificity (Sp) of diagnostic test system, desired minimum detectable prevalence, precision, population size, and desired power of the survey. In addition, sample sizes to detect FMD if the disease is present and also as proof of freedom were computed. The current FMD active surveillance programs consist of clinical, virological, and serological surveillance. For the 2012 serological surveillance, annual sample sizes (n = 265,065) are planned at four separate levels: statistical (n = 60,884) and targeted (n = 115,232) at breeding pig farms and slaughter house, in together with the detection of structural proteins (SP) antibodies against FMD (n = 88,949). Overall, the sample size was not designed taking the specific aims of each surveillance stream into account. The sample sizes for statistical surveillance, assuming stratified two-stage sampling technique, was based to detect at least one FMD-infected case in the general population. The resulting sample size can be used to obtain evidence of freedom from FMD infection, not for detecting animals that have antibodies against FMD virus non-structural proteins (NSP). Additionally, sample sizes for targeted surveillance were not aimed for the population at risk, and also without consideration of statistical point of view. To at least the author's knowledge, sampling plan for targeted, breeding pig farms and slaughter house is not necessary and need to be included in the part of statistical surveillance. Assuming design prevalence of 10% in an infinite population, a total of 29 animals are required to detect at least one positive with probability of 95%, using perfect diagnostic test system (Se = Sp = 100%). A total of 57,211 animals needed to be sampled to give 95% confidence of estimating SP prevalence of 80% at the individual animal-level with a precision of ${\pm}5%$, assuming 800 herds with an average 200 heads per farm, within-farm variance of 0.2, between-farm variance of 0.05, cost ratio of 100:1 of farm against animals. Furthermore, 779,736 animals were required to demonstrate FMD freedom, and the sample size can further be reduced depending on the parameters assumed.

• Journal of the Korean Society of Safety
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• v.12 no.3
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• pp.60-66
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• 1997

In this paper, a moving object surveillance system, which can extract moving object in real-time, using image subtraction method is described. This technique based on the novelty filter having the structure of neural network associative memory. Digital arithmetic and timing control parts were composed of hardwired controller to treat two-dimensional massive image information. SRAMS having 20 ns access time were used for the image buffer that has high speed write/read property. Image extraction algorithm is discussed and supported by simulation and experiments.

• International Journal of Railway
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• v.2 no.1
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• pp.18-21
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• 2009

The basis of modem risk-based safety management is to focus on what might happen and ensure it is designed out of the system by robust hazard identification and risk analysis. However, in the real world things go wrong and it is essential to be prepared for the worst so that the response can minimise harm and loss of property and damage to the environment. Whilst some hazard mitigation measures are aimed at preventing incidents, others are venting escalation. The results of the tests concluded that the most effective means by the control room, both with and without, local station staff assistance using directive public address announcements and CCTV surveillance.

• Proceedings of the Korean Nuclear Society Conference
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• 1999.05a
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• pp.455-455
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• 1999

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.3
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• pp.202-208
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• 2013

In the image processing for VS (Video Surveillance), the detection of moving entities in a monitored scene is an important step. A background subtraction technique has been widely employed to find the moving entities. However, the extracted foreground regions often include not only real entities but also their cast shadows, and this can cause errors in following image processing steps, such as tracking, recognition, and analysis. In this paper, a novel technique is proposed to determine the shadow pixels of moving objects in the foreground image of a VS camera. Compared to existing techniques where the same decision criteria are applied to all moving pixels, the proposed technique determines shadow pixels using local features based on two facts: First, the amount of pixel intensity drop due to a shadow depends on the intensity level of background. Second, the distribution pattern of pixel intensities remains even if a shadow is cast. The proposed method has been tested at various situations with different backgrounds and moving humans in different colors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.8
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• pp.731-737
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• 2014

This paper presents abnormal behavior detection in crowd within surveillance video. We have defined below two cases as a abnormal behavior; first as a sporadically spread phenomenon and second as a sudden running in same direction. In order to detect these two abnormal behaviors, we first extract the motion vector and propose a new descriptor which is combined MHOF(Multi-scale Histogram of Optical Flow) and DCHOF(Directional Change Histogram of Optical Flow). Also, binary classifier SVM(Support Vector Machine) is used for detection. The accuracy of the proposed algorithm is evaluated by both UMN and PETS 2009 dataset and comparisons with the state-of-the-art method validate the advantages of our algorithm.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.153-160
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• 2011

Recently, the use of security surveillance system including CCTV is increasing due to the increase of terrors and crimes. At the same time, interest of face recognition at a distance using surveillance cameras has been increasing. Accordingly, we analyzed the performance of face recognition according to distance using PCA-based face recognition and interpolation. In this paper, we used Nearest, Bilinear, Bicubic, Lanczos3 interpolations to interpolate face image. As a result, we confirmed that existing interpolation have an few effect on performance of PCA-based face recognition and performance of PCA-based face recognition is improved by including face image according to distance in traning data.