• Title/Summary/Keyword: real time video surveillance

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Real-Time Transcoding and Advanced Encryption for 360 CCTV Streaming

  • Le, Tuan Thanh;Jeong, JongBeom;Lee, Soonbin;Jang, Dongmin;Ryu, Il-Woong;Ryu, Eun-Seok
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2019.06a
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    • pp.144-146
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    • 2019
  • Recently, according to the rapid development of surveillance information, closed-circuit television (CCTV) has become an indispensable component in security systems. A lot of advanced technologies of encryption and compression are implementing to improve the performance and security levels of the CCTV system. Especially, 360 video CCTV streaming is promising for surveillance without blind areas. However, compared to previous systems, 360 CCTV requires large bandwidth and low latency. Therefore, it requires more efficiently effort to improve the CCTV system performance. In order to meet the demands of 360 CCTV streaming, transcoding is an essential process to enhance the current CCTV system. Moreover, encryption algorithm is also an important priority in security system. In this paper, we propose a real-time transcoding solution in combination with the ARIA and AES algorithms. Experimental results prove that the proposed method has achieved around 195% speed up transcoding compared to FFMPEG libx265 method. Furthermore, the proposed system can handle multiple transcoding sessions simultaneously at high performance for both live 360 CCTV system and existing CCTV system.

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Implementation of a unified live streaming based on HTML5 for an IP camera (IP 카메라를 위한 HTML5 기반 통합형 Live Streaming 구현)

  • Ryu, Hong-Nam;Yang, Gil-Jin;Kim, Jong-Hun;Choi, Byoung-Wook
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.28 no.9
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    • pp.99-104
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    • 2014
  • This paper presents a unified live-streaming method based on Hypertext Mark-up Language 5(HTML5) for an IP camera which is independent of browsers of clients and is implemented with open-source libraries. Currently, conventional security systems based on analog CCTV cameras are being modified to newer surveillance systems utilizing IP cameras. These cameras offer remote surveillance and monitoring regardless of the device being used at any time, from any location. However, this approach needs live-streaming protocols to be implemented in order to verify real-time video streams and surveillance is possible after installation of separate plug-ins or special software. Recently, live streaming is being conducted through HTML5 using two different standard protocols: HLS and DASH, that works with Apple and Android products respectively. This paper proposes a live-streaming approach that is linked on either of the two protocols which makes the system independent with the browser or OS. The client is possible to monitor real-time video streams without the need of any additional plug-ins. Moreover, by implementing open source libraries, development costs and time were economized. We verified usefulness of the proposed approach through mobile devices and extendability to other various applications of the system.

Graph-based Moving Object Detection and Tracking in an H.264/SVC bitstream domain for Video Surveillance (감시 비디오를 위한 H.264/SVC 비트스트림 영역에서의 그래프 기반 움직임 객체 검출 및 추적)

  • Sabirin, Houari;Kim, Munchurl
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2012.07a
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    • pp.298-301
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    • 2012
  • This paper presents a graph-based method of detecting and tracking moving objects in H.264/SVC bitstreams for video surveillance applications that makes use the information from spatial base and enhancement layers of the bitstreams. In the base layer, segmentation of real moving objects are first performed using a spatio-temporal graph by removing false detected objects via graph pruning and graph projection, followed by graph matching to precisely identify the real moving objects over time even under occlusion. For the accurate detection and reliable tracking of moving objects in the enhancement layer, as well as saving computational complexity, the identified block groups of the real moving objects in the base layer are then mapped to the enhancement layer to provide accurate and efficient object detection and tracking in the bitstreams of higher resolution. Experimental results show the proposed method can produce reliable results with low computational complexity in both spatial layers of H.264/SVC test bitstreams.

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Smartphone Real Time Streaming Service using Parallel TCP Transmission (병렬 TCP 통신을 이용한 스마트폰 실시간 스트리밍 서비스)

  • Kim, Jang-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.5
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    • pp.937-941
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    • 2016
  • This paper proposed an efficient multiple TCP mechanism using Android smartphones for remote control video Wi-Fi stream transmission via network communications in real time. The wireless video stream transmission mechanism can be applied in various area such as real time server stream transmissions, movable drones, disaster robotics and real time security monitoring systems. Moreover, we urgently need to transmit data in timely fashion such as medical emergency, security surveillance and disaster prevention. Our parallel TCP transmission system can play an important role in several area such as real time server stream transmissions, movable drones, disaster robotics and real time security monitoring systems as mentioned in the previous sentence. Therefore, we designed and implemented a parallel TCP transmission (parallel stream) for an efficient real time video streaming services. In conclusion, we evaluated proposed mechanism using parallel TCP transmission under various environments with performance analysis.

Indoor Surveillance Camera based Human Centric Lighting Control for Smart Building Lighting Management

  • Yoon, Sung Hoon;Lee, Kil Soo;Cha, Jae Sang;Mariappan, Vinayagam;Lee, Min Woo;Woo, Deok Gun;Kim, Jeong Uk
    • International Journal of Advanced Culture Technology
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    • v.8 no.1
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    • pp.207-212
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    • 2020
  • The human centric lighting (HCL) control is a major focus point of the smart lighting system design to provide energy efficient and people mood rhythmic motivation lighting in smart buildings. This paper proposes the HCL control using indoor surveillance camera to improve the human motivation and well-beings in the indoor environments like residential and industrial buildings. In this proposed approach, the indoor surveillance camera video streams are used to predict the day lights and occupancy, occupancy specific emotional features predictions using the advanced computer vision techniques, and this human centric features are transmitted to the smart building light management system. The smart building light management system connected with internet of things (IoT) featured lighting devices and controls the light illumination of the objective human specific lighting devices. The proposed concept experimental model implemented using RGB LED lighting devices connected with IoT features open-source controller in the network along with networked video surveillance solution. The experiment results are verified with custom made automatic lighting control demon application integrated with OpenCV framework based computer vision methods to predict the human centric features and based on the estimated features the lighting illumination level and colors are controlled automatically. The experiment results received from the demon system are analyzed and used for the real-time development of a lighting system control strategy.

Aerial Video Summarization Approach based on Sensor Operation Mode for Real-time Context Recognition (실시간 상황 인식을 위한 센서 운용 모드 기반 항공 영상 요약 기법)

  • Lee, Jun-Pyo
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.6
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    • pp.87-97
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    • 2015
  • An Aerial video summarization is not only the key to effective browsing video within a limited time, but also an embedded cue to efficiently congregative situation awareness acquired by unmanned aerial vehicle. Different with previous works, we utilize sensor operation mode of unmanned aerial vehicle, which is global, local, and focused surveillance mode in order for accurately summarizing the aerial video considering flight and surveillance/reconnaissance environments. In focused mode, we propose the moving-react tracking method which utilizes the partitioning motion vector and spatiotemporal saliency map to detect and track the interest moving object continuously. In our simulation result, the key frames are correctly detected for aerial video summarization according to the sensor operation mode of aerial vehicle and finally, we verify the efficiency of video summarization using the proposed mothed.

A Study of CCTV Video Tracking Technique to The Object Monitoring in The Automation Manufacturing Facilities (자동화 생산 시설물의 객체모니터링을 위한 CCTV 영상추적 기술에 관한 연구)

  • Seo, Won-Gi;Lee, Ju-Young;Park, Goo-Man;Shin, Jae-Kwon;Lee, Seung-Youn
    • Journal of Satellite, Information and Communications
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    • v.7 no.1
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    • pp.134-138
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    • 2012
  • In this paper, we implement the real-time status monitoring system to surveil the object in the automation manufacturing facilities and we propose the CCTV video tracking system using the video tracking filter to improve efficiency. To surveil the object in automation manufacturing facilities, we implement monitoring SW on the based of the video tracking filter instead of the general method for the video monitoring so the reliable monitoring based on the PC is possible efficiently. In addition, accessibility and convenience for administrator are improved as the real-time status confirmation function. Also, we conform the performance improvement effect through the performance analysis of the proposed monitoring system using the video tracking filter.

Abnormal Crowd Behavior Detection Using Heuristic Search and Motion Awareness

  • Usman, Imran;Albesher, Abdulaziz A.
    • International Journal of Computer Science & Network Security
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    • v.21 no.4
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    • pp.131-139
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    • 2021
  • In current time, anomaly detection is the primary concern of the administrative authorities. Suspicious activity identification is shifting from a human operator to a machine-assisted monitoring in order to assist the human operator and react to an unexpected incident quickly. These automatic surveillance systems face many challenges due to the intrinsic complex characteristics of video sequences and foreground human motion patterns. In this paper, we propose a novel approach to detect anomalous human activity using a hybrid approach of statistical model and Genetic Programming. The feature-set of local motion patterns is generated by a statistical model from the video data in an unsupervised way. This features set is inserted to an enhanced Genetic Programming based classifier to classify normal and abnormal patterns. The experiments are performed using publicly available benchmark datasets under different real-life scenarios. Results show that the proposed methodology is capable to detect and locate the anomalous activity in the real time. The accuracy of the proposed scheme exceeds those of the existing state of the art in term of anomalous activity detection.

Secure Camera Network System for Intelligent Surveillance Systems Based on Real-Time Video (실시간 영상 기반의 지능형 보안 관제 시스템을 위한 안전한 카메라 네트워크 시스템)

  • Yang, Soo-mi;Ko, Eun-kyung
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.6
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    • pp.1102-1106
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    • 2015
  • To provide social security and for cooperative smart camera context awareness processing, each camera stores and exchange context data. For a specific event, measured values with other context data is stored RDB. RDB is transformed to ontology RDF file and is used for context reasoning. Interoperability between smart cameras conforms to ONVIF and constitutes intelligent surveillance system. To guarantee the confidentiality and integrity, securiy techniques are adopted. Security overhead between agents is analyzed in the prototype system implemented.

Detection and Recognition of Illegally Parked Vehicles Based on an Adaptive Gaussian Mixture Model and a Seed Fill Algorithm

  • Sarker, Md. Mostafa Kamal;Weihua, Cai;Song, Moon Kyou
    • Journal of information and communication convergence engineering
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    • v.13 no.3
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    • pp.197-204
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    • 2015
  • In this paper, we present an algorithm for the detection of illegally parked vehicles based on a combination of some image processing algorithms. A digital camera is fixed in the illegal parking region to capture the video frames. An adaptive Gaussian mixture model (GMM) is used for background subtraction in a complex environment to identify the regions of moving objects in our test video. Stationary objects are detected by using the pixel-level features in time sequences. A stationary vehicle is detected by using the local features of the object, and thus, information about illegally parked vehicles is successfully obtained. An automatic alarm system can be utilized according to the different regulations of different illegal parking regions. The results of this study obtained using a test video sequence of a real-time traffic scene show that the proposed method is effective.