• 제목/요약/키워드: Object surveillance

검색결과 377건 처리시간 0.026초

영상정보의 저장 공간 관리를 위한 동적/정적 객체 분리 및 시각암호화 메커니즘 (Dynamic / Static Object Segmentation and Visual Encryption Mechanism for Storage Space Management of Image Information)

  • 김진수;박남제
    • 한국멀티미디어학회논문지
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    • 제22권10호
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    • pp.1199-1207
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    • 2019
  • Video surveillance data, which is used for preemptive or post-emptive action against any event or accident, is required for monitoring the location, but is reducing the capacity of the image data by removing intervals for cost reduction and system persistence. Such a video surveillance system is fixed in a certain position and monitors the area only within a limited angle, or monitors only the fixed area without changing the angle. At this time, the video surveillance system that is monitored only within a limited angle shows that the variation object such as the floating population shows different status in the image, and the background of the image maintains a generally constant appearance. The static objects in the image do not need to be stored in all the images, unlike the dynamic objects that must be continuously shot, and occupy a storage space other than the necessary ones. In this paper, we propose a mechanism to analyze the image, store only the small size image for the fixed background, and store it as image data only for variable objects.

지능형 보안 감시 시스템을 위한 높이 예측 메커니즘 (Height Prediction Mechanism for Smart Surveillance Systems)

  • 심재석;임유진
    • 정보처리학회논문지:컴퓨터 및 통신 시스템
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    • 제3권7호
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    • pp.241-244
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    • 2014
  • 오늘날 Wireless Sensor Network(WSN)은 보안 감시 시스템의 주요 부분으로 자리 잡고 있다. 이러한 WSN 기반 보안 감시 시스템에서는 감시 대상 영역 내에서 특정한 이벤트의 발생이나 대상체(object)의 발견 및 그 위치를 파악하는 것이 중요하다. 특히 허가받지 않은 외부인의 침입을 감시하는 시스템에서 애완동물이나 설치류 등으로 인한 거짓 경보(false alarm)의 발생은 시스템의 신뢰도를 떨어뜨리게 된다. 따라서 본 논문에서는 감지된 대상체가 사람인지 여부를 판단하기 위하여, 감지된 대상체의 높이를 예측하는 메커니즘을 제안한다. 또한 제안한 메커니즘의 성능분석을 위하여 여러 가지 시나리오에서 예측 정확도를 측정하였다.

영상 Subtraction을 이용한 이동 물체 감시 시스템 (Moving Object Surveillance System based on Image Subtraction Technique)

  • 이승현;류충상
    • 한국안전학회지
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    • 제12권3호
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    • pp.60-66
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    • 1997
  • In this paper, a moving object surveillance system, which can extract moving object in real-time, using image subtraction method is described. This technique based on the novelty filter having the structure of neural network associative memory. Digital arithmetic and timing control parts were composed of hardwired controller to treat two-dimensional massive image information. SRAMS having 20 ns access time were used for the image buffer that has high speed write/read property. Image extraction algorithm is discussed and supported by simulation and experiments.

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Object segmentation and object-based surveillance video indexing

  • Kim, Jin-Woong;Kim, Mun-Churl;Lee, Kyu-Won;Kim, Jae-Gon;Ahn, Chie-Teuk
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 1999년도 KOBA 방송기술 워크샵 KOBA Broadcasting Technology Workshop
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    • pp.165.1-170
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    • 1999
  • Object segmentation fro natural video scenes has recently become one of very active research to pics due to the object-based video coding standard MPEG-4. Object detection and isolation is also useful for object-based indexing and search of video content, which is a goal of the emerging new standard, MPEG-7. In this paper, an automatic segmentation method of moving objects in image sequence is presented which is applicable to multimedia content authoring for MPEG-4, and two different segmentation approaches suitable for surveillance applications are addressed in raw data domain and compressed bitstream domains. We also propose an object-based video description scheme based on object segmentation for video indexing purposes.

A Study on Swarm Robot-Based Invader-Enclosing Technique on Multiple Distributed Object Environments

  • Ko, Kwang-Eun;Park, Seung-Min;Park, Jun-Heong;Sim, Kwee-Bo
    • Journal of Electrical Engineering and Technology
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    • 제6권6호
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    • pp.806-816
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    • 2011
  • Interest about social security has recently increased in favor of safety for infrastructure. In addition, advances in computer vision and pattern recognition research are leading to video-based surveillance systems with improved scene analysis capabilities. However, such video surveillance systems, which are controlled by human operators, cannot actively cope with dynamic and anomalous events, such as having an invader in the corporate, commercial, or public sectors. For this reason, intelligent surveillance systems are increasingly needed to provide active social security services. In this study, we propose a core technique for intelligent surveillance system that is based on swarm robot technology. We present techniques for invader enclosing using swarm robots based on multiple distributed object environment. The proposed methods are composed of three main stages: location estimation of the object, specified object tracking, and decision of the cooperative behavior of the swarm robots. By using particle filter, object tracking and location estimation procedures are performed and a specified enclosing point for the swarm robots is located on the interactive positions in their coordinate system. Furthermore, the cooperative behaviors of the swarm robots are determined via the result of path navigation based on the combination of potential field and wall-following methods. The results of each stage are combined into the swarm robot-based invader-enclosing technique on multiple distributed object environments. Finally, several simulation results are provided to further discuss and verify the accuracy and effectiveness of the proposed techniques.

서베일런스 네트워크에서 적응적 색상 모델을 기초로 한 실시간 객체 추적 알고리즘 (Real-Time Object Tracking Algorithm based on Adaptive Color Model in Surveillance Networks)

  • 강성관;이정현
    • 디지털융복합연구
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    • 제13권9호
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    • pp.183-189
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    • 2015
  • 본 논문은 서베일런스 네트워크에서 영상의 색상 정보를 이용한 객체 추적 방법을 제안한다. 이 방법은 적응적인 색상 모델을 이용한 객체 검출을 수행한다. 객체 윤곽선 검출은 객체 인식과 같은 응용에서 중요한 역할을 수행한다. 실험 결과는 색상과 크기에서 객체의 다양한 변화가 있을 때에도 성공적인 객체 검출을 증명한다. 실시간으로 객체를 검출하는 응용 분야에서 대량의 영상 데이터를 전송할 때 색상 분포의 형태를 찾아내는 것이 가능하다. 객체의 특정 색상 정보는 입력 영상에서 동적으로 변화하는 색상에서 자주 수정되어진다. 그래서, 이 알고리즘은 해당 추적 영역 안에서 객체의 추적 영역 정보를 탐지하고 그 객체의 움직임만을 추적한다. 실험을 통해, 본 논문은 어떤 이상적인 상황하에서 제안하는 객체 추적 알고리즘이 다른 방법보다 더 강인한 면이 있다는 것을 보여준다.

Study on a Robust Object Tracking Algorithm Based on Improved SURF Method with CamShift

  • Ahn, Hyochang;Shin, In-Kyoung
    • 한국컴퓨터정보학회논문지
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    • 제23권1호
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    • pp.41-48
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    • 2018
  • Recently, surveillance systems are widely used, and one of the key technologies in this surveillance system is to recognize and track objects. In order to track a moving object robustly and efficiently in a complex environment, it is necessary to extract the feature points in the interesting object and to track the object using the feature points. In this paper, we propose a method to track interesting objects in real time by eliminating unnecessary information from objects, generating feature point descriptors using only key feature points, and reducing computational complexity for object recognition. Experimental results show that the proposed method is faster and more robust than conventional methods, and can accurately track objects in various environments.

도시철도 환경에 적합한 지능형 감시카메라 시나리오의 연구 (A Study of Scenario in Intelligent Surveillance Camera for Urban Transit)

  • 장일식;정철준;김형민;안태기;박구만
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2009년도 춘계학술대회 논문집
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    • pp.866-871
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    • 2009
  • In this paper, we introduced design of intelligent surveillance camera system and typical event processing scenario for urban transit. To analyze video, we studied events that frequently occur in surveillance camera system. Scenario is designed for estimation in the case of seven representative situations(designated area invasion, an object left alone, removed object in designated area, object tracking, loitering and congestion measurement) in urban transit. Our system is optimized for low hardware complexity, real time processing and scenario dependent solution.

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무인감시장치 구현을 위한 단일 이동물체 추적 알고리즘 (A Single Moving Object Tracking Algorithm for an Implementation of Unmanned Surveillance System)

  • 이규원;김영호;이재구;박규태
    • 전자공학회논문지B
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    • 제32B권11호
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    • pp.1405-1416
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    • 1995
  • An effective algorithm for implementation of unmanned surveillance system which detects moving object from image sequences, predicts the direction of it, and drives the camera in real time is proposed. Outputs of proposed algorithm are coordinates of location of moving object, and they are converted to the values according to camera model. As a pre- processing, extraction of moving object and shape discrimination are performed. Existence of the moving object or scene change is detected by computing the temporal derivatives of consecutive two or more images in a sequence, and this result of derivatives is combined with the edge map from one original gray level image to obtain the position of moving object. Shape discri-mination(Target identification) is performed by analysis of distribution of projection profiles in x and y directions. To reduce the prediction error due to the fact that the motion cha- racteristic of walking man may have an abrupt change of moving direction, an order adaptive lattice structured linear predictor is proposed.

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지능형 감시를 위한 객체추출 및 추적시스템 설계 및 구현 (A Study on the Object Extraction and Tracking System for Intelligent Surveillance)

  • 장태우;신용태;김종배
    • 한국통신학회논문지
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    • 제38B권7호
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    • pp.589-595
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    • 2013
  • 최근 보안 관제를 위한 인원부족 및 감시 능력의 한계로 자동화된 지능형 관제 시스템에 대한 요구가 증가하고 있다. 이 논문에서는 지능형 감시시스템의 구축을 위하여 자동화된 객체추출 및 추적 시스템, 그리고 이상행위를 인지하는 이상행위 검출 시스템을 설계하고 구현하였다. 각 모듈은 기존의 연구 결과를 바탕으로 실제 환경에서 적용되고 상용화가 가능하도록 알고리즘의 성능을 높였으며, 구현 후 다양한 테스트를 통해 그 성과를 검증하였다. 특히, 배회 또는 도주와 같은 이상행위의 경우 1초 이내에 검출할 수 있었다.