• Title/Summary/Keyword: Surveillance video

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Video-based Intelligent Unmanned Fire Surveillance System (영상기반 지능형 무인 화재감시 시스템)

  • Jeon, Hyoung-Seok;Yeom, Dong-Hae;Joo, Young-Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.4
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    • pp.516-521
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    • 2010
  • In this paper, we propose a video-based intelligent unmanned fire surveillance system using fuzzy color models. In general, to detect heat or smoke, a separate device is required for a fire surveillance system, this system, however, can be implemented by using widely used CCTV, which does not need separate devices and extra cost. The systems called video-based fire surveillance systems use mainly a method extracting smoke or flame from an input image only. The smoke is difficult to extract at night because of its gray-scale color, and the flame color depends on the temperature, the inflammable, the size of flame, etc, which makes it hard to extract the flame region from the input image. This paper deals with a intelligent fire surveillance system which is robust against the variation of the flame color, especially at night. The proposed system extracts the moving object from the input image, makes a decision whether the object is the flame or not by means of the color obtained by fuzzy color model and the shape obtained by histogram, and issues a fire alarm when the flame is spread. Finally, we verify the efficiency of the proposed system through the experiment of the controlled real fire.

Real-Time Surveillance of People on an Embedded DSP-Platform

  • Qiao, Qifeng;Peng, Yu;Zhang, Dali
    • Journal of Ubiquitous Convergence Technology
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    • v.1 no.1
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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.

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Design and Implementation of U-city Infrared Image Surveillance System (U-city 적외선 영상 감시 시스템의 설계 및 구현)

  • Kim, Won-Ho;Jang, Bok-Kyu
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.10a
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    • pp.561-564
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    • 2009
  • This paper present design and implementation of U-city infrared image surveillance system based on the digital media processor. The hardware is designed and implemented by using commercial chips such as DM642 processor and video encoder, video decoder and the functions of software are to analyze temperature distribution of a monitoring image and to monitor disaster situation such as fire. The required functions and performances are confirmed by testing of the prototype and we verified practicality of the system.

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Activity-based key-frame detection and video summarization in a wide-area surveillance system (광범위한 지역 감시시스템에서의 행동기반 키프레임 검출 및 비디오 요약)

  • Kwon, Hye-Young;Lee, Kyoung-Mi
    • Journal of Internet Computing and Services
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    • v.9 no.3
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    • pp.169-178
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    • 2008
  • In this paper, we propose a video summarization system which is based on activity in video acquired by multiple non-overlapping cameras for wide-area surveillance. The proposed system separates persons by time-independent background removal and detects activities of the segmented persons by their motions. In this paper, we extract eleven activities based on whose direction the persons move to and consider a key-frame as a frame which contains a meaningful activity. The proposed system summarizes based on activity-based key-frames and controls an amount of summarization according to an amount of activities. Thus the system can summarize videos by camera, time, and activity.

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Rainfall Recognition from Road Surveillance Videos Using TSN (TSN을 이용한 도로 감시 카메라 영상의 강우량 인식 방법)

  • Li, Zhun;Hyeon, Jonghwan;Choi, Ho-Jin
    • Journal of Korean Society for Atmospheric Environment
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    • v.34 no.5
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    • pp.735-747
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    • 2018
  • Rainfall depth is an important meteorological information. Generally, high spatial resolution rainfall data such as road-level rainfall data are more beneficial. However, it is expensive to set up sufficient Automatic Weather Systems to get the road-level rainfall data. In this paper, we propose to use deep learning to recognize rainfall depth from road surveillance videos. To achieve this goal, we collect a new video dataset and propose a procedure to calculate refined rainfall depth from the original meteorological data. We also propose to utilize the differential frame as well as the optical flow image for better recognition of rainfall depth. Under the Temporal Segment Networks framework, the experimental results show that the combination of the video frame and the differential frame is a superior solution for the rainfall depth recognition. The final model is able to achieve high performance in the single-location low sensitivity classification task and reasonable accuracy in the higher sensitivity classification task for both the single-location and the multi-location case.

Implementation of Real-Time Multi-Camera Video Surveillance System with Automatic Resolution Control Using Motion Detection (움직임 감지를 사용하여 영상 해상도를 자동 제어하는 실시간 다중 카메라 영상 감시 시스템의 구현)

  • Jung, Seulkee;Lee, Jong-Bae;Lee, Seongsoo
    • Journal of IKEEE
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    • v.18 no.4
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    • pp.612-619
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    • 2014
  • This paper proposes a real-time multi-camera video surveillance system with automatic resolution control using motion detection. In ordinary times, it acquires 4 channels of QVGA images, and it merges them into single VGA image and transmit it. When motion is detected, it automatically increases the resolution of motion-occurring channel to VGA and decreases those of 3 other channels to QQVGA, and then these images are overlaid and transmitted. Thus, it can magnifies and watches the motion-occurring channel while maintaining transmission bandwidth and monitoring all other channels. When it is synthesized with 0.18 um technology, the maximum operating frequency is 110 MHz, which can theoretically support 4 HD cameras.

Flame detection algorithm using adaptive threshold in thermal video (적응 문턱치를 이용한 열영상 화염 검출 알고리즘)

  • Jeong, Soo-Young;Kim, Won-Ho
    • Journal of Satellite, Information and Communications
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    • v.9 no.4
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    • pp.91-96
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    • 2014
  • This paper proposed an adaptive threshold method for detecting flame candidate regions in a infrared image and it adapts according to the contrast and intensity changes in the image. Conventional flame detection systems uses fixed threshold method since surveillance environment does not change, once the system installed. But it needs a adaptive threshold method as requirements of surveillance system has changed. The proposed adaptive threshold algorithm uses the dynamic behavior of flame as featured parameter. The test result is analysed by comparing test result of proposed adaptive threshold algorithm and conventional fixed threshold method. The analysed data shows, the proposed method has 91.42% of correct detection rate and false detection is reduced by 20% comparing to the conventional method.

Sub-Frame Analysis-based Object Detection for Real-Time Video Surveillance

  • Jang, Bum-Suk;Lee, Sang-Hyun
    • International Journal of Internet, Broadcasting and Communication
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    • v.11 no.4
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    • pp.76-85
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    • 2019
  • We introduce a vision-based object detection method for real-time video surveillance system in low-end edge computing environments. Recently, the accuracy of object detection has been improved due to the performance of approaches based on deep learning algorithm such as Region Convolutional Neural Network(R-CNN) which has two stage for inferencing. On the other hand, one stage detection algorithms such as single-shot detection (SSD) and you only look once (YOLO) have been developed at the expense of some accuracy and can be used for real-time systems. However, high-performance hardware such as General-Purpose computing on Graphics Processing Unit(GPGPU) is required to still achieve excellent object detection performance and speed. To address hardware requirement that is burdensome to low-end edge computing environments, We propose sub-frame analysis method for the object detection. In specific, We divide a whole image frame into smaller ones then inference them on Convolutional Neural Network (CNN) based image detection network, which is much faster than conventional network designed forfull frame image. We reduced its computationalrequirementsignificantly without losing throughput and object detection accuracy with the proposed method.

Security Framework for Intelligent Predictive Surveillance Systems (지능형 예측감시 시스템을 위한 보안 프레임워크)

  • Park, Jeonghun;Park, Namje
    • Journal of the Korea Convergence Society
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    • v.11 no.3
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    • pp.77-83
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    • 2020
  • Recently, intelligent predictive surveillance system has emerged. It is a system that can probabilistically predict the future situation and event based on the existing data beyond the scope of the current object or object motion and situation recognition. Since such intelligent predictive monitoring system has a high possibility of handling personal information, security consideration is essential for protecting personal information. The existing video surveillance framework has limitations in terms of privacy. In this paper, we proposed a security framework for intelligent predictive surveillance system. In the proposed method, detailed components for each unit are specified by dividing them into terminals, transmission, monitoring, and monitoring layers. In particular, it supports active personal information protection in the video surveillance process by supporting detailed access control and de-identification.

Using Bluetooth Module for Real-time Image Surveillance System (Bluetooth Module을 이용한 실시간 영상감시 시스템)

  • Seo, Yoon-Seok;Kwak, Jae-Hyuk;Lim, Joon-Hong
    • Proceedings of the KIEE Conference
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    • 2005.10b
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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.

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