• International journal of advanced smart convergence
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• 제9권4호
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• pp.120-123
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• 2020

The surveillance system to prevent crime and accidents in advance has become a necessity, not an option in real life. Not only public institutions but also individuals are installing surveillance cameras to protect their property and privacy. However, since the installed surveillance camera cannot be monitored for 24 hours, the focus is on the technology that tracks the video after an accident occurs rather than prevention. In this paper, we propose a system model that monitors abnormal behaviors that may cause crimes through real-time video, and when a specific behavior occurs, the surveillance system automatically detects it and responds immediately through an alarm. We are a model that analyzes real-time images from surveillance cameras and uses I3D models from analysis servers to analyze abnormal behavior and deliver notifications to web servers and then to clients. If the system is implemented with the proposed model, immediate response can be expected when a crime occurs.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.337-339
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• 2005

The demand for a real-time image surveillance system using network camera server is increasing as the network infra has been grown and digital video compression techniques have been developed. The image surveillance system using network camera server has several merits compared to existing real-time image surveillance system using CCTV. It would be more convenient if wireless realtime image transmission were possible. In this paper, a bluetooth module is designed and implemented for a real-time image surveillance system to send and receive informations wirelessly. It may simplify the system development procedures and increase the productivity by low power consumption, low cost, and simple wireless installation. A scatter-net formation is proposed using dynamic and distributed algorithm so that the network connection is reliable.

• 인터넷정보학회논문지
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• 제7권3호
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• pp.107-118
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• 2006

네트워크 인프라의 성장과 디지털 영상압축 기술의 발달로 네트워크 카메라 서버를 이용한 실시간 영상감시 시스템의 수요가 증가하고 있다. 기존의 CCTV를 이용한 실시간 영상감시에 비해 네트워크 카메라 서버를 이용한 영상감시는 많은 이점이 있다. 본 논문에선 실시간 영상감시 시스템의 핵심 모듈로서 JPEG 영상의 수집과 전달을 담당하는 JPEG Streamer의 모델을 제시하고 이를 설계, 구현한다. JPEG Streamer의 안정성과 효율성을 위해서 쓰레드 풀과 공유 메모리를 사용했다. 실시간 영상의 품질을 높이기 위해서 더블 버퍼링의 개념을 도입했다. 이렇게 구현된 JPEG Streamer를 실시간 영상감시 시스템의 개발에 이용함으로써 생산성을 높일 수 있을 뿐 아니라, 신뢰성과 안정성도 확보 할 수 있다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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• pp.317-320
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• 2003

In this paper, we present real-time, accurate face region detection and tracking technique for an intelligent surveillance system. It is very important to obtain the high-resolution images, which enables accurate identification of an object-of-interest. Conventional surveillance or security systems, however, usually provide poor image quality because they use one or more fixed cameras and keep recording scenes without any clue. We implemented a real-time surveillance system that tracks a moving person using pan-tilt-zoom (PTZ) cameras. While tracking, the region-of-interest (ROI) can be obtained by using a low-pass filter and background subtraction. Color information in the ROI is updated to extract features for optimal tracking and zooming. The experiment with real human faces showed highly acceptable results in the sense of both accuracy and computational efficiency.

• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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• pp.123-126
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• 2005

Wireless Sensor Networks will revolutionize applications such as environmental monitoring, home automation, and logistics. We developed forest fire surveillance system. In this paper, Considering the fact that in Korea, during November to May, forest fires occur very frequently causing catastrophic damages on the valuable environment, Although exists other forest fire surveillance system such as surveillance camera tower, infrared ray sensor system and satellite system. Preexistence surveillance system can't real-time surveillance, monitoring, database and automatic alarm. But, forest fire surveillance system(FFSS) support above. In this paper, we describes a system development approach for a wireless sensor network based FFSS that is to be used to measure temperature and humidity as well as being fitted with a smoke detector. Such a device can be used as an early warning fire detection system and real-time surveillance in the area of a bush fire or endangered public infrastructure. Once the system has being development, a mesh network topology will be implemented with the chosen sensor node with the aim of developing a sophisticated mesh network.

• ETRI Journal
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• 제37권3호
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• pp.551-561
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• 2015

We propose a novel multiple-object tracking algorithm for real-time intelligent video surveillance. We adopt particle filtering as our tracking framework. Background modeling and subtraction are used to generate a region of interest. A two-step pedestrian detection is employed to reduce the computation time of the algorithm, and an iterative particle repropagation method is proposed to enhance its tracking accuracy. A matching score for greedy data association is proposed to assign the detection results of the two-step pedestrian detector to trackers. Various experimental results demonstrate that the proposed algorithm tracks multiple objects accurately and precisely in real time.

• Journal of Ubiquitous Convergence Technology
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• 제1권1호
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• pp.3-8
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• 2007

This paper presents a set of techniques used in a real-time visual surveillance system. The system is implemented on a low-cost embedded DSP platform that is designed to work with stationary video sources. It consists of detection, a tracking and a classification module. The detector uses a statistical method to establish the background model and extract the foreground pixels. These pixels are grouped into blobs which are classified into single person, people in a group and other objects by the dynamic periodicity analysis. The tracking module uses mean shift algorithm to locate the target position. The system aims to control the human density in the surveilled scene and detect what happens abnormally. The major advantage of this system is the real-time capability and it only requires a video stream without other additional sensors. We evaluate the system in the real application, for example monitoring the subway entrance and the building hall, and the results prove the system's superior performance.

• 한국멀티미디어학회논문지
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• 제18권11호
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• pp.1289-1301
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• 2015

Pedestrian detection (PD) is an essential task in various applications and sliding window-based methods utilizing HOG (Histogram of Oriented Gradients) or HOG-like descriptors have been shown to be very effective for accurate PD. However, due to exhaustive search across images, PD methods based on sliding window usually require heavy computational time. In this paper, we propose a real-time PD method for embedded visual surveillance with fixed backgrounds. The proposed PD method employs HOG descriptors as many PD methods does, but utilizes selective search so that it can save processing time significantly. The proposed selective search is guided by restricting searching to candidate regions extracted from Adaptive Gaussian Mixture Model (AGMM)-based background subtraction technique. Moreover, approximate computation of HOG descriptor and implementation in fixed-point arithmetic mode contributes to reduction of processing time further. Possible accuracy degradation due to approximate computation is compensated by applying an appropriate one among three offline trained SVM classifiers according to sizes of candidate regions. The experimental results show that the proposed PD method significantly improves processing speed without noticeable accuracy degradation compared to the original HOG-based PD and HOG with cascade SVM so that it is a suitable real-time PD implementation for embedded surveillance systems.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.628-631
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• 2003

In this paper, we present real-time, accurate face region detection and tracking technique for an intelligent surveillance system. It is very important to obtain the high-resolution images, which enables accurate identification of an object-of-interest. Conventional surveillance or security systems, however, usually provide poor image quality because they use one or more fixed cameras and keep recording scenes without any cine. We implemented a real-time surveillance system that tracks a moving person using four pan-tilt-zoom (PTZ) cameras. While tracking, the region-of-interest (ROI) can be obtained by using a low-pass filter and background subtraction. Color information in the ROI is updated to extract features for optimal tracking and zooming. The experiment with real human faces showed highly acceptable results in the sense of both accuracy and computational efficiency.

• 한국인터넷방송통신학회논문지
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• 제14권1호
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• pp.169-177
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• 2014

DVR 및 NVR을 이용한 디지털 저장매체를 영상감시 시스템에서 활용하게 되면서 영상처리 모듈의 개발은 영상 보안 시장의 필수적인 요소이다. 특히 네트워크 카메라의 등장은 기존 아날로그 방식의 CCTV를 대체하면서 영상처리 모듈 개발의 필요성을 더욱 부각시키고 있다. 본 논문에서는 움직임 감지 기법을 이용한 영상 감시 서버를 설계 및 구축하고 서버에서 처리되는 영상처리 결과를 실시간으로 모바일 디바이스에서 확인 가능한 영상감시 시스템을 개발하였다. 영상처리를 위해 리눅스 기반의 서버에 오픈소스 OpenCV를 활용한 영상처리 모듈을 개발하였고, 네트워크 카메라로부터 전송되는 실시간 비디오 데이터를 저장 및 가공하여 안드로이드기반 모바일 기기에서 검색 가능한 영상감시 시스템을 구축하였다.