• Title/Summary/Keyword: Surveillance Video

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Military surveillance System design using Digital video Recording Camera (디지털 녹화 감시 카메라 시스템에 의한 군사 방위 시스템 설계)

  • 조혜진;홍충효;최연성;김선우
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2003.05a
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    • pp.175-178
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    • 2003
  • In this paper, proposed system use real-time MPEG-2 compression, and retrieve video from the storage using efficient indexed algorithm. System survey wide military range, diffuse situation to adjacent units, and transmit images long distance.

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Panoramic Video Generation Method Based on Foreground Extraction (전경 추출에 기반한 파노라마 비디오 생성 기법)

  • Kim, Sang-Hwan;Kim, Chang-Su
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.2
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    • pp.441-445
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    • 2011
  • In this paper, we propose an algorithm for generating panoramic videos using fixed multiple cameras. We estimate a background image from each camera. Then we calculate perspective relationships between images using extracted feature points. To eliminate stitching errors due to different image depths, we process background images and foreground images separately in the overlap regions between adjacent cameras by projecting regions of foreground images selectively. The proposed algorithm can be used to enhance the efficiency and convenience of wide-area surveillance systems.

Ramdomg Hash for Integrity Verification Method of Multimedia Data in Surveillance System (비디오 감시 장치 무결성 검증을 위한 랜덤 해시 방법)

  • Ghimire, Sarala;Lee, Bumshik
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2019.11a
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    • pp.165-168
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    • 2019
  • The advancement in technology has led to the enormous use of multimedia applications. The video/image recorded by such applications provides critical information that can be used as a visual evidence. However, owing to the adequacy in using different editing tools, it is susceptible to malicious alterations. Thus, the reliability or the integrity of the visual information should be verified before using it as an evidence. In this paper, we propose an integrity verification method for the surveillance system using randomized hashing. The integrity value of the surveillance data is generated using the randomized hashing and elliptic curve cryptography (ECC), which is used later for the validation. The experimental results obtained from the embedded accident data recorder (ADR) system shows that the proposed method is very efficient and provides a high level of security.

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Development of Intelligent Surveillance System Using Stationary Camera for Multi-Target-Based Object Tracking (다중영역기반의 객체추적을 위한 고정형 카메라를 이용한 지능형 감시 시스템 개발)

  • Im, Jae-Hyun;Kim, Tae-Kyung;Choi, Kwang-Yong;Han, In-Kyo;Paik, Joon-Ki
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.789-790
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    • 2008
  • In this paper, we introduce the multi-target-based auto surveillance algorithm. Multi-target-based surveillance system detects intrusion objects in the specified areas. The proposed algorithm can divide into two parts: i) background generation, ii) object extraction. In this paper, one of the optical flow equation methods for estimation of gradient method used to generate the background [2]. In addition, the objects and back- ground video images that are continually entering the differential extraction.

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Dividing Occluded Pedestrians in Wide Angle Images for the Vision-Based Surveillance and Monitoring (시각 기반 감시 및 관측을 위한 광각 영상에서의 중첩된 보행자 구분)

  • Park, Jaehyeong;Do, Yongtae
    • Journal of Sensor Science and Technology
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    • v.24 no.1
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    • pp.54-61
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    • 2015
  • In recent years, there has been increasing use of automatic surveillance and monitoring systems based on vision sensors. Humans are often the most important target in the systems, but processing human images is difficult due to the small sizes and flexible motions. Particularly, occlusion among pedestrians in camera images brings practical problems. In this paper, we propose a novel method to separate image regions of occluded pedestrians. A camera equipped with a wide angle lens is attached to the ceiling of a building corridor for sensing pedestrians with a wide field of view. The output images of the camera are processed for the human detection, tracking, identification, distortion correction, and occlusion handling. We resolve the occlusion problem adaptively depending on the angles and positions of their heads. Experimental results showed that the proposed method is more efficient and accurate compared with existing methods.

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

  • Chang, Il-Sik;Jeong, Cheol-Jun;Kim, Hyung-Min;An, Tae-Ki;Park, Goo-Man
    • Proceedings of the KSR Conference
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    • 2009.05a
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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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Dividing Occluded Humans Based on an Artificial Neural Network for the Vision of a Surveillance Robot (감시용 로봇의 시각을 위한 인공 신경망 기반 겹친 사람의 구분)

  • Do, Yong-Tae
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.5
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    • pp.505-510
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    • 2009
  • In recent years the space where a robot works has been expanding to the human space unlike traditional industrial robots that work only at fixed positions apart from humans. A human in the recent situation may be the owner of a robot or the target in a robotic application. This paper deals with the latter case; when a robot vision system is employed to monitor humans for a surveillance application, each person in a scene needs to be identified. Humans, however, often move together, and occlusions between them occur frequently. Although this problem has not been seriously tackled in relevant literature, it brings difficulty into later image analysis steps such as tracking and scene understanding. In this paper, a probabilistic neural network is employed to learn the patterns of the best dividing position along the top pixels of an image region of partly occlude people. As this method uses only shape information from an image, it is simple and can be implemented in real time.

Enhanced Image Encryption Scheme using Context Adaptive Variable Length Coding (적응 산술 부호화를 이용한 고화질 영상 암호화 전략)

  • Shim, Gab-Yong;Lee, Malrey
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.13 no.3
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    • pp.119-126
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    • 2013
  • Achieve real-time encryption and video data transcoding, current video encryption methods usually integrate encryption algorithm with video compression course. This paper is devoted to discussing the video encryption technology, by encrypting to avoid unauthorized person getting video data. This paper studied the H.264 entropy coding and proposed of CAVLC video encryption scheme which is combined with the process of entropy coding of H.264 CAVLC encryption scheme. Three encryption levels are proposed. In addition, a scrambling method is also proposed which makes the encrypted frames more robust in anti crack. This method showed more robust video data encryption function and compressive rate.

Robust Real-time Detection of Abandoned Objects using a Dual Background Model

  • Park, Hyeseung;Park, Seungchul;Joo, Youngbok
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.2
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    • pp.771-788
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    • 2020
  • Detection of abandoned objects for smart video surveillance should be robust and accurate in various situations with low computational costs. This paper presents a new algorithm for abandoned object detection based on the dual background model. Through the template registration of a candidate stationary object and presence authentication methods presented in this paper, we can handle some complex cases such as occlusions, illumination changes, long-term abandonment, and owner's re-attendance as well as general detection of abandoned objects. The proposed algorithm also analyzes video frames at specific intervals rather than consecutive video frames to reduce the computational overhead. For performance evaluation, we experimented with the algorithm using the well-known PETS2006, ABODA datasets, and our video dataset in a live streaming environment, which shows that the proposed algorithm works well in various situations.

SUPER RESOLUTION RECONSTRUCTION FROM IMAGE SEQUENCE

  • Park Jae-Min;Kim Byung-Guk
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.197-200
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    • 2005
  • Super resolution image reconstruction method refers to image processing algorithms that produce a high resolution(HR) image from observed several low resolution(LR) images of the same scene. This method is proved to be useful in many practical cases where multiple frames of the same scene can be obtained, such as satellite imaging, video surveillance, video enhancement and restoration, digital mosaicking, and medical imaging. In this paper we applied super resolution reconstruction method in spatial domain to video sequences. Test images are adjacently sampled images from continuous video sequences and overlapped for high rate. We constructed the observation model between the HR images and LR images applied by the Maximum A Posteriori(MAP) reconstruction method that is one of the major methods in the super resolution grid construction. Based on this method, we reconstructed high resolution images from low resolution images and compared the results with those from other known interpolation methods.

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