• Journal of the Institute of Convergence Signal Processing
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• v.10 no.2
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• pp.112-119
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• 2009

This paper describes a robust visual surveillance algorithm under outdoor environment. One of the difficult problems for outdoor is to obtain effective updating process of background images. Because background images generally contain the shadows of buildings, trees, moving clouds and other objects, they are changed by lapse of time and variation of illumination. They provide the lowering of performance for surveillance system under outdoor. In this paper, a robust algorithm for visual surveillance system under outdoor is proposed, which apply the mixture Gaussian filter and color invariant property on pixel level to update background images. In results, it was showed that the moving objects can be detected on various shadows under outdoor.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.1006-1018
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• 2020

Dataset is getting more import to develop a learning based algorithm. Quality of the algorithm definitely depends on dataset. So we introduce new dataset over 200 thousands images which are fully labeled multi modal sensor data. Proposed dataset was designed and constructed for researchers who want to develop detection, tracking, and action classification in outdoor environment for surveillance scenarios. The dataset includes various images and multi modal sensor data under different weather and lighting condition. Therefor, we hope it will be very helpful to develop more robust algorithm for systems equipped with difference kinds of sensors in outdoor application. Case studies with the proposed dataset are also discussed in this paper.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.5
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• pp.11-20
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• 2019

Recently, our society is increasingly aware of the strengthening of 'publicness'. In particular, it is urgent to improve safety in that public spaces are used by an unspecified number of people. Therefore, the purpose of this study is to derive an indicators for evaluating crime safety in outdoor public spaces and to present the relative weights of each evaluation indicator. For this purpose, this study investigated the relative importance of crime safety evaluation indicators for outdoor public spaces to experts and conducted AHP analysis based on this. The result of this study is as follows. First, it was confirmed that similar tendency was observed among experts group (researcher, public officials, planner) related to outdoor public space. Therefore, the results of this study will be a certain reference point in the future social consensus on the issue. Second, the experts related to physical environment evaluation showed that the priority of environmental planning related to 'Natural surveillance' is highly evaluated in order to increase crime safety of outdoor public space. Next, it was recognized that 'Mechanical surveillance' and 'Legibility reinforcement' were needed.

• Korean Institute of Interior Design Journal
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• v.22 no.2
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• pp.211-219
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• 2013

The purpose of this study is to propose the environmental planning guidelines of elementary school settings for a crime safety. The research methodologies To achieve the goal, the literature review analysis and the survey were used as main research methodologies. The survey is organized as follows. First, elementary education facilities were divided into 20 spaces based on the major space. Second, after analyzing the domestic and foreign CPTED Guidelines, elements of environmental planning were classified to fit in the space. Based on this, the expert survey was conducted. The results of this study are as follows; First, it is necessary to consider specific places such as 'toilets', 'parking lot', 'in-between space', 'main access road', 'sub-access road' and 'harmful facilities around school' for safer school environment. Second, it is significant to plan 'equipment facilities' and 'outdoor space in the school setting' with priority for elementary education environment. Third, environmental planning elements for safer elementary schools can be classified into 9 factors(types) including 'natural surveillance planning', 'territoriality reinforcement planning', 'mechanical surveillance planning', 'access control planning' and 'neighborhood reinforcement planning'. Forth, regarding 'indoor space', crime-free elementary school environment can be build through 'natural surveillance planning' and 'territoriality reinforcement planning'. Finally, regarding 'outdoor space', the crime can be prevented through 'natural surveillance planning' and 'access control planning'.

• ETRI Journal
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• v.35 no.1
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• pp.80-88
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• 2013

A passive infrared or pyroelectric infrared (PIR) sensor is mainly used to sense the existence of moving objects in an indoor environment. However, in an outdoor environment, there are often outbreaks of false alarms from environmental changes and other sources. Therefore, it is difficult to provide reliable detection outdoors. In this paper, two algorithms are proposed to reduce false alarms and provide trustworthy quality to surveillance systems. We gather PIR signals outdoors, analyze the collected data, and extract the target features defined as window energy and alarm duration. Using these features, we model target and false alarms, from which we propose two target decision algorithms: window energy detection and alarm duration detection. Simulation results using real PIR signals show the performance of the proposed algorithms.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.103-110
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• 2012

The population growth along with the urbanization, has caused more problems in many public areas, such as subway airport terminals, hospital, etc. Many surveillance systems have been installed in the public areas, but not all of those can be monitored in real-time, because the operators that observe the monitors are very small compared with the number of the monitors. For example, the observer can miss some crucial accidents or detect after considerable delays. Thus, intelligent surveillance system for preventing the accidents are needed, such as Intelligent Surveillance Systems. in this paper, we propose a new crowd density estimation method which aims at estimating moving crowd using images from surveillance cameras situated in outdoor locations. The moving crowd is estimated from the area where using optical flow. The edge information is also used as feature to measure the crowd density, so we improve the accuracy of estimation of crowd density. A multilayer neural network is designed to classify crowd density into 5 classes. Finally the proposed method is experimented with PETS 2009 images.

• Journal of the Korean Institute of Educational Facilities
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• v.20 no.2
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• pp.33-42
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• 2013

Due to the lack of available site in urban setting outdoor space in elementary schools are getting smaller and tend to be replaced by indoor spaces. Focusing on courtyard, piloti space and roof space, this study analyzed the current condition and usage of the outdoor spaces in the urban mini-schools based on the analysis of architectural drawing, interview, survey, and observation. Following issues are found for appropriate planning for outdoor spaces in the urban mini-schools. Firstly, roof space needs to be coordinated with the physical education and outdoor class curriculum and should be planned separately for quiet activities. Secondly, the piloti space should be planned as an independent space rather than a connection between classroom and outdoor space, with appropriate surveillance from teacher's space for the lower graders. Thirdly, courtyard space, typical space in urban mini school surrounded by densely arranged buildings, should be thermally controlled for outdoor class or resting with appropriate screen from noise to keep quiet atmosphere.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.65-70
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• 2018

This paper describes a effective information compressor algorithm for the fourth industrial technology. One of the difficult problems for outdoor is to obtain effective updating process of background images. Because input images generally contain the shadows of buildings, trees, moving clouds and other objects, they are changed by lapse of time and variation of illumination. They provide the lowering of performance for surveillance system under outdoor. In this paper, a effective information algorithm for variable environment variable under outdoor is proposed, which apply the Kalman Estimation Modeling and adaptive threshold on pixel level to separate foreground and background images from current input image. In results, the better SNR of about 3dB~5dB and about 10%~25% noise distribution rate in the proposed method. Furthermore, it was showed that the moving objects can be detected on various shadows under outdoor and better result Information.

• Electronics and Telecommunications Trends
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• v.37 no.1
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• pp.1-9
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• 2022

With the development of artificial intelligence, many studies have focused on evaluating abnormal situations by using various sensors, as industries try to automate some of the surveillance and security tasks traditionally performed by humans. In particular, mobile robots using multimodal sensors are being used for pilot operations aimed at helping security robots cope with various outdoor situations. Multiagent systems, which combine fixed and mobile systems, can provide more efficient coverage (than that provided by other systems), but network bottlenecks resulting from increased data processing and communication are encountered. In this report, we will examine recent trends in object recognition and abnormal-situation determination in various changing outdoor security robot environments, and describe an outdoor security robot platform that operates as a multiagent equipped with a multimodal sensor.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.237-240
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• 2001

An image processing and decision making method for the Automatic Surveillance System is proposed. The aim of our Automatic Surveillance System is to detect a moving object and make a decision on whether it is human or not. Various object features such as the ratio of the width and the length of the moving object, the distance dispersion between the principal axis and the object contour, the eigenvectors, the symmetric axes, and the areas if the segmented region are used in this paper. These features are not the unique and decisive characteristics for representing human Also, due to the outdoor image property, the object feature information is unavoidably vague and inaccurate. In order to make an efficient decision from the information, we use a fuzzy rules base system ai an approximate reasoning method. The fuzzy rules, combining various object features, are able to describe the conditions for making an intelligent decision. The fuzzy rule base system is initially constructed by heuristic approach and then, trained and tasted with input/output data Experimental result are shown, demonstrating the validity of our system.