JKSCI
Trend of Technology in Video Surveillance System
1)
Jaemin Song*, Arum Park*, Sae Bom Lee*
*Research Professor, Big Data Research Center, Kyung Hee University, Seoul, Korea
*Research Professor, Big Data Research Center, Kyung Hee University, Seoul, Korea
*Research Professor, Big Data Research Center, Kyung Hee University, Seoul, Korea
[Abstract]
Video surveillance is consists of cameras, transmission devices, storage and playback devices, and is used for crime prevention and disaster monitoring. Recently, it has been spreading to a wide variety of fields, and has developed into an intelligent video surveillance system that can automatically recognize or track characteristic objects of people and things. The purpose of this study was to investigate the cases of video surveillance service applying the latest technology by dividing it into the home, public, and private sectors. also this study tried to investigate and research what advantage it brings from a business perspective. By looking at the cases introduced in this study, it was confirmed that the viedo security service is developing intelligently, such as excellent compatibility with CCTV, multiple video surveillance, CCTV screen motion detection, and alarm through automatic analysis.
▸Key words: Video surveillance, Intelligence system, Smart home security service, Video management system
[요 약]
영상보안은 카메라 , 전송장치, 저장 및 재생장치 등으로 구성되며 범죄예방, 재난 감시 등에 사 용되고 있다. 최근 매우 다양한 분야로 파급되고 있으며, 자동으로 사람 및 사물의 특징적인 객체 를 인식하거나 추적할 수 있는 지능형 영상보안 시스템으로 발전하고 있다 . 본 연구는 홈과 공공 부문 , 민간부문으로 구분하여 최신 기술을 적용한 영상보안 서비스 사례들을 조사하고 비즈니스 관점에서 어떠한 이점을 가져다주는지 조사·연구하고자 하였다. 본 연구에서 소개한 사례들을 살 펴봄으로써 뛰어난 CCTV와의 호환, 여러 개의 영상감시, CCTV 촬영 화면 모션 감지, 자동 분석 을 통한 알람 제공 등 영상보안 서비스가 지능적으로 발전하고 있다는 것을 확인할 수 있었다 .
▸주제어: 영상보안, 지능형 시스템, 스마트홈 보안 서비스, 동영상 관리 시스템
∙First Author: Jamin Song, Corresponding Author: Sae Bom Lee
*Jaemin Song ([email protected]), Big Data Research Center, Kyung Hee University *Arum Park ([email protected]), Big Data Research Center, Kyung Hee University *Sae Bom Lee ([email protected]), Big Data Research Center, Kyung Hee University
∙Received: 2020. 04. 24, Revised: 2020. 06. 05, Accepted: 2020. 06. 08.
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