• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.155-158
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• 2019

최근 지능형 CCTV 관제 시스템에 대한 수요가 증가하고 있다. CCTV 영상 데이터의 양이 폭발적으로 증가하고 있어 이를 분석하기 위한 기술의 발전이 필요한 실정이다. 대부분의 지능형 CCTV 관제 시스템은 영상 속 객체를 찾고 이 객체의 메타데이터를 통해 지능형 관제 시스템을 수행한다. 하지만 영상 속 객체의 로그가 항상 정확하지 않다. 현재의 객체 인식 기술로는 CCTV 영상의 밝기, 해상도 조건에 따라 성능의 차이가 심하고, 영상의 프레임 대비 빠르게 움직인 CCTV 영상 속 모든 객체를 사람이 인식하는 정도로 인식하기 어렵다. 이러한 이동 객체의 크기, 위치를 분석한 메타데이터에는 에러가 포함되기 쉽다. 본 논문에서는 지능형 CCTV 관제 시스템에서 분석한 영상 속 객체의 프레임 메타데이터 에러를 학습기반 실시간 에러 필터링 알고리즘을 통해 개선하여 에러가 필터링된 데이터를 사용하는 지능형 관제 시스템의 정확도 향상에 기여 할 것을 기대한다.

• Journal of the Society of Disaster Information
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• v.10 no.1
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• pp.105-115
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• 2014

In this research, we developed video analytic algorithms to detect water-level automatically and a system for proactive alarming using intelligent CCTV cameras. We applied these algorithms and a system to test-beds and verified for practical use. We made camera-selection policies and operation plans to keep the detection accuracy high and to optimize the suitability for the ever-changing weather condition, while the environmental factors such as camera shaking and weather condition can affect to detection accuracy. The estimation result of algorithms showed 90% detection accuracy for all CCTV camera types. For water level detection, NIR camera performed great. NIR camera performed over 95% accuracy in day or night, suitable in natural weather condition such as shaking condition, fog, and low light, needs similar installment skills with common cameras, and spends only 15% high cost. As a result, we practically tested water level detection algorithms and operation system based on intelligent CCTV camera. Furthermore, we expect the positive evidences when it is applied for public use.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.105-106
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• 2016

본 논문에서는 방범용 CCTV 시스템의 빈번한 장애를 처리하는데 원격지 방문으로 소요되는 시간과 인력의 소모를 개선하기 위해 모니터링 및 단순장애 자가 처리 기능을 탑재한 방범용 CCTV를 위한 지능형 모니터링 시스템을 제안한다. 지능형 모니터링 시스템은 센서 모듈에서 측정된 값을 지능형 모니터링 모듈에서 취합하고 모니터링 하여 자가 처리 여부를 판단하고, 이에 따라 제어모듈과 통신하거나 상황실에 알림 등의 여부를 판단하여, 네트워크를 통해 원격으로 방범용 CCTV의 상태를 모니터링하고 장애발생을 예측하여 자가 처리 하거나 원격 처리할 수 있다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.346-348
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• 2022

Many CCTVs are needed to monitor a physically large area. When installing CCTV indoors, the wiring environment is sufficient, so many CCTVs can be installed. However, wiring is relatively difficult outdoors. In addition, when monitoring a long distance, wiring costs to the monitoring site are incurred. Therefore, when installing CCTV at a physically long distance, it is necessary to apply wireless technology. In this study, the structure of the existing CCTV system was checked and the requirements for converting it to a wireless environment were derived. And according to the requirements, a wireless-based intelligent CCTV system was proposed. As a result, it was confirmed that the wireless-based intelligent CCTV proposed in this study operates normally in a wireless environment. This study was conducted based on the wifi environment, and additional research is needed to extend it to the mobile mobile telecommunication environment.

• Convergence Security Journal
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• v.23 no.5
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• pp.117-123
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• 2023

Recently, as the demand for Generative Artificial Intelligence (AI) and artificial intelligence has increased, the seriousness of misuse and abuse has emerged. However, intelligent CCTV, which maximizes detection of abnormal behavior, is of great help to prevent crime in the military and police. AI performs learning as taught by humans and then proceeds with self-learning. Since AI makes judgments according to the learned results, it is necessary to clearly understand the characteristics of learning. However, it is often difficult to visually judge strange and abnormal behaviors that are ambiguous even for humans to judge. It is very difficult to learn this with the eyes of artificial intelligence, and the result of learning is very many False Positive, False Negative, and True Negative. In response, this paper presented standards and methods for clarifying the learning of AI's strange and abnormal behaviors, and presented learning measures to maximize the judgment ability of intelligent CCTV's False Positive, False Negative, and True Negative. Through this paper, it is expected that the artificial intelligence engine performance of intelligent CCTV currently in use can be maximized, and the ratio of False Positive and False Negative can be minimized..

• Journal of Digital Convergence
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• v.11 no.10
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• pp.359-366
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• 2013

Due to the development and market expansion of image analysis and recognition technology, video security such as CCTV cameras and digital storage devices, are required for real-time monitoring systems and intelligent video security systems. This includes the development of more advanced technologies. A rotatable PTZ camera, in a CCTV camera system, has a zoom function so you can acquire a precise picture. However it can cause blind spots, and can not monitor two or more moving objects at the same time. This study concerns, the intelligent tracking of multiple moving objects, CCTV systems, and methods of video surveillance. An intelligent video surveillance system is proposed. It can accurately shoot broad areas and track multiple objects at the same time, much more effectively than using one fixed camera for an entire area or two or more PTZ cameras.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.203-204
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• 2023

The construction industry is a hazardous environment in which many field workers work. Therefore, there is a limit to the safety manager's grasp of all situations. In order to solve these problems, the application of automatic control technology in connection with AI and CCTV is being introduced, and the development of intelligent CCTV to reduce the safety accident rate is actively progressing. This study seeks to present future directions by identifying the current status of intelligent CCTV developed to reduce the safety accident rate at construction sites and analyzing its limitations. Through this, the range of accident prevention types of the safety control system at the construction site will be confirmed and the need for future intelligent CCTV function development will be suggested.

• The Journal of Korean Institute of Information Technology
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• v.17 no.10
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• pp.101-113
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• 2019

Recently, the intelligent video surveillance technology has become able to provide various services such as predictive surveillance that have not been provided previously. Securing the security of the intelligent video surveillance is essential, and malicious manipulation of the original CCTV video data can lead to serious social problems. Therefore, in this paper, we proposed an intelligent video surveillance environment based on blockchain. The proposed scheme guarantees the integrity of the CCTV image data and protects the ROI privacy through the edge blockchain, so there is no privacy exposure of the object. In addition, it is effective because it is possible to increase the transmission efficiency and reduce storage by enabling video deduplication.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.966-967
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• 2015

영상감시, 특히 CCTV는 이미 보안에서 없어서는 안 될 큰 중심이 된지 오래지만 지속적인 기술 성장 못지않게 또 다른 첨단기술 및 기능 요구가 증가되고 있으며 그중에 하나가 CCTV 영상의 사각지대이다. CCTV는 다양한 목적을 위해 24시간 영상을 녹화하지만 현재 시스템으로 사각지대 없는 CCTV시스템은 다수의 카메라를 설치하여만 한다. 이는 높은 비용과 유지관리가 필요하게 되어 적재적소에 CCTV시스템 설치가 어려운 실정이다. 따라서 본 연구개발에서는 사각지대가 없는 CCTV 개발에 필요한 지능형 영상분석 시스템에 필요한 통합 관리 시스템을 설계하여 전체적인 시스템 개발 완료에 목표를 두고 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.7
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• pp.589-595
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• 2013

The agents for security surveillance are not enough for monitoring CCTV system, so the intelligent automatic surveillance system is needed. In this paper, object detection, tracking and abnormal event detection system is implemented for intelligent CCTV system. Each modules are tested on the real CCTV environment and promoted for commercialization. Abnormal event detection module and loitering detection and sudden running detection function and it's detection time is under 1 second which is satisfied level.