• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.1047-1048
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• 2014

본 논문에서는 CCTV의 문제점 및 설치 취약지역의 재난 발생을 사전에 예방하기 위해 무인비행체와 객체 인식 기술에 대해 조사 및 분석하고 이를 토대로 무인비행체의 영상정보 데이터를 관제기관에서 받아와 객체 인식 및 패턴 분석을 통해 재난을 예방하는 시스템을 설계하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.379-380
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• 2022

KAIST 캠퍼스 기반의 실습환경 구축을 위하여 캠퍼스 전체를 스마트시티 테스트베드로 사용하며 CCTV 네트워크 기반 모니터링/관제 시스템 구축, 교통, 방범, 가로등, CCTV, 교내 버스 등 인프라 통합 관제 및 보안 실습실 구축하고 교내 자율주행 기술 연구진과 실습 협력 추진을 통한 캠퍼스 기반의 실전 스마트 환경을 토대로 다각도의 보안 공격/방어 실습을 진행하고 지자체 및 컨소시엄 기업들과 산학협력 프로젝트를 진행하기 위하여 구축한 내용을 설명한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.225-227
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• 2022

Now In Seoul, about 75,000 CCTVs are installed in 25 district offices. Each ward office in Seoul has built a control center for CCTV control and is building information such as people, vehicle types, license plate recognition and color classification into big data through 24-hour artificial intelligence intelligent image analysis. Seoul Metropolitan Government has signed MOUs with the Ministry of Land, Infrastructure and Transport, the National Police Agency, the Fire Service, the Ministry of Justice, and the military base to enable rapid response to emergency/emergency situations. In other words, we are building a smart city that is safe and can prevent disasters by providing CCTV images of each ward office. In this paper, the CCTV image is designed to extract the characteristics of the vehicle and personnel when an incident occurs through artificial intelligence, and based on this, predict the escape route and enable continuous tracking. It is designed so that the AI automatically selects and displays the CCTV image of the route. It is designed to expand the smart city integration platform by providing image information and extracted information to the adjacent ward office when the escape route of a person or vehicle related to an incident is expected to an area other than the relevant jurisdiction. This paper will contribute as basic data to the development of smart city integrated platform research.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.117-128
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• 2013

u-safety service system inter-works with the diverse operation agencies, through CCTV network, such as the emergency call terminal with built-in GPS, the mobile communication network, u-safety service provider, relay system and CCTV control center. In the case of the emergency call, this service searches the location of caller in real time, and then continues to search the location of caller through the control of CCTV in the searched place, and can provide the several agencies like guardian, police office, fire station, hospitals, relief organizations and municipalities, with the diverse information necessary for the secure rescue through SMS and wired network. In this paper, a new protocol and specification for u-safety service relay system is designed and implemented. The effectiveness of presented protocol is verified by computer simulation. The designed protocol of u-safety service is applied to real 3GPP and 3GPP2 mobile communication networks to verify its performance.

• KIISE Transactions on Computing Practices
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• v.24 no.3
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• pp.151-156
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• 2018

In this paper, a method to classify objects in outdoor CCTV images using Convolutional Neural Network(CNN) and background subtraction is proposed. Object candidates are extracted using background subtraction and they are classified with CNN to detect objects in the image. At the end, computation complexity is highly reduced in comparison to other object detection algorithms. A database is constructed by filming alleys and playgrounds, places where crime occurs mainly. In experiments, different image sizes and experimental settings are tested to construct a best classifier detecting person. And the final classification accuracy became 80% for same camera data and 67.5% for a different camera.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.9
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• pp.1779-1786
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• 2009

Due to increased terrors and crimes, the use of surveillance camera systems including CCTV is also increasing. Private information such as faces or behavior patterns can be recorded in CCTV and when it is exposed, it may cause infringement to privacy and crimes. This paper analyses conventional methods on protection of privacy in surveillance camera system and then suggests an RFID-based surveillance camera system that can both watch crimes and protect privacy. The proposed system protects privacy and watches crimes using scrambling and an RFID system.

• Journal of Industrial Convergence
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• v.18 no.3
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• pp.53-61
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• 2020

Travel speed is an important parameter for measuring road traffic and incident detection system. In this paper I suggests a model developed for estimating reliable and accurate average roadway link travel speeds using image processing sensor. This method extracts the vehicles from the video image from CCTV, tracks the moving vehicles using deep neural network, and extracts traffic information such as link travel speeds and volume. The algorithm estimates link travel speeds using a robust data-fusion procedure to provide accurate link travel speeds and traffic information to the public. In the field tests, the new model performed better than existing methods.

• Electronics and Telecommunications Trends
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• v.35 no.2
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• pp.17-27
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• 2020

Predicting where and when a crime may occur in an area of interest is one of many strategies of predictive policing. Multidimensional analysis, including CCTV, can overcome the limitations of hotspot prediction, especially of violent crimes. In order to identify the precursors of a crime, it is necessary to analyze dynamic data such as attributes and activities of people, social information, environmental information, traffic flows, and weather. These parameters can be recognized by CCTV. In addition, it provides accurate analysis of the circumstances of a crime in a dynamic situation, calculates the risk, and predicts the probability of a crime occurring in the near future. Additionally, it provides ways to gather historical criminal datasets, including sensitive personal information.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.3
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• pp.83-90
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• 2010

In modern society, there has been an increase in needs to protect the life and property of the people, because the number of various crimes is on the increase due to the sudden and complicated changes of the urban environment. For the needs, security persons in the urban area are expanding the role and skill of police for more effective crime prevention and surveillance, although the number of policeman/woman is insufficient and their tasks are hard. Recently, a system to observe and prevent crime in effective has been introduced by using such an artificial surveillance device as CCTV to monitor focusing on one area for 24 hours. However, the system brings such problems as the insufficiency of systematic criteria to install surveillance device and the invasion of privacy. Therefore, in this study, artificial surveillance zones to monitor crimes are selected by applying spatial features between artificial surveillance devices including CCTV and crime occurrence place, and using GIS spatial analysis techniques. As a result of selecting, it's found that the number of CCTV is absolutely insufficient and spatial distribution is not fully considered in the existing location of installed CCTV.

• The Journal of Bigdata
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• v.6 no.2
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• pp.125-137
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• 2021

The number of CCTV installed in Korea is over 1.3 million, increasing by more than 15% annually. However, due to the limited budget compared to the installation demand, the infrastructure is composed of 500,000 pixel low-quality CCTV, and there is a limits on identification of objects in the video. Public CCTV has high utility in various fields such as crime prevention, traffic information collection (control), facility management, and fire prevention. Especially, since installed in high height, it works as its role in solving diverse crime and is in increasing trend. However, the current public CCTV field is operated with potential problems such as inability to identify due to environmental factors such as fog, snow, and rain, and the low-quality of collected images due to the installation of low-quality CCTV. Therefore, in this study, in order to remove the typical low-quality elements of public CCTV, the method of attenuating scattered light in the image caused by dust, water droplets, fog, etc and algorithm application method which uses deep-learning algorithm to improve input video into videos over quality over 4K are suggested.