• Title/Summary/Keyword: Embedded Surveillance

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Multiple-Background Model-Based Object Detection for Fixed-Embedded Surveillance System (고정형 임베디드 감시 카메라 시스템을 위한 다중 배경모델기반 객체검출)

  • Park, Su-In;Kim, Min Young
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.11
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    • pp.989-995
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    • 2015
  • Due to the recent increase of the importance and demand of security services, the importance of a surveillance monitor system that makes an automatic security system possible is increasing. As the market for surveillance monitor systems is growing, price competitiveness is becoming important. As a result of this trend, surveillance monitor systems based on an embedded system are widely used. In this paper, an object detection algorithm based on an embedded system for a surveillance monitor system is introduced. To apply the object detection algorithm to the embedded system, the most important issue is the efficient use of resources, such as memory and processors. Therefore, designing an appropriate algorithm considering the limit of resources is required. The proposed algorithm uses two background models; therefore, the embedded system is designed to have two independent processors. One processor checks the sub-background models for if there are any changes with high update frequency, and another processor makes the main background model, which is used for object detection. In this way, a background model will be made with images that have no objects to detect and improve the object detection performance. The object detection algorithm utilizes one-dimensional histogram distribution, which makes the detection faster. The proposed object detection algorithm works fast and accurately even in a low-priced embedded system.

A Study on Optimization of Intelligent Video Surveillance System based on Embedded Module (임베디드 모듈 기반 지능형 영상감시 시스템의 최적화에 관한 연구)

  • Kim, Jin Su;Kim, Min-Gu;Pan, Sung Bum
    • Smart Media Journal
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    • v.7 no.2
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    • pp.40-46
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    • 2018
  • The conventional CCTV surveillance system for preventing accidents and incidents misses 95% of the data after 22 minutes where one person monitors multiple CCTV. To address this issue, researchers have studied the computer-based intelligent video surveillance system for notifying people of the abnormal situation. However, because the system is involved in the problems of power consumption and costs, the intelligent video surveillance system based on embedded modules has been studied. This paper implements the intelligent video surveillance system based on embedded modules for detecting intruders, detecting fires and detecting loitering, falling. Moreover, the algorithm and the embedded module optimization method are applied to implement real-time processing. The intelligent video surveillance system based on embedded modules is implemented in Raspberry Pi. The algorithm processing time is 0.95 seconds on Raspberry Pi before optimization, and 0.47 seconds on Raspberry Pi after optimization, reduced processing time by 50.52%. Therefore, this suggests real processing possibility of the intelligent video surveillance system based on the embedded modules is possible.

Implementation of an Intelligent Visual Surveillance System Based on Embedded System (임베디드 시스템 기반 지능형 영상 감시 시스템 구현)

  • Song, Jae-Min;Kim, Dong-Jin;Jung, Yong-Bae;Park, Young-Seak;Kim, Tae-Hyo
    • Journal of the Institute of Convergence Signal Processing
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    • v.13 no.2
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    • pp.83-90
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    • 2012
  • In this paper, an intelligent visual surveillance system based on a NIOS II embedded platform is implemented. By this time, embedded based visual surveillance systems were restricted for a special purpose because of high dependence upon hardware. In order to improve the restriction, we implement a flexible embedded platform, which is available for various purpose of applications. For high speed processing of software based programming, we improved performance of the system which is integrated the SOPC type of NIOS II embedded processor and image processing algorithms by using software programming and C2H(The Altera NIOS II C-To-Hardware(C2H) Acceleration Compiler) compiler in the core of the hardware platform. Then, we constructed a server system which globally manage some devices by the NIOS II embedded processor platform, and included the control function on networks to increase efficiency for user. We tested and evaluated our system at the designated region for visual surveillance.

Multi-layer Surveillance System based on Wireless Mesh Networks (무선 메쉬 네트워크 기반의 다층구조 감시 시스템 구축)

  • Yoon, Tae-Ho;Song, Yoo-Seoung
    • IEMEK Journal of Embedded Systems and Applications
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    • v.7 no.5
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    • pp.209-217
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    • 2012
  • In the present, Wireless Sensor Network(WSN) has been used for the purpose of the military operation with surveillance systems and for collecting useful information from the natural environment. Basically, low-power, easy deployment and low cost are the most important factors to be deployed for WSNs. Lots of researches have been studied to meet those requirements, especially on the node capacity and battery lifetime improvements. Recently, the study of wireless mesh networks applied into the surveillance systems has been proceeded as a solution of easy deployment. In this paper, we proposed large-scale intelligent multi-layer surveillance systems based on QoS assuring Wireless Mesh Networks and implemented them in the real testbed environment. The proposed system explains functions and operations for each subsystem as well as S/W and H/W architectures. Experimental results are shown for the implemented subsystems and the performance is satisfactory for the surveillance system. We can identify the possibility of the implemented multi-layer surveillance system to be used in practice.

Emphasizing Intelligent Event Processing Cooperative Surveillance System (지능형 사건 처리를 강조한 협업 감시 시스템)

  • Yoon, Tae-Ho;Song, Yoo-Seoung
    • IEMEK Journal of Embedded Systems and Applications
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    • v.7 no.6
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    • pp.339-343
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    • 2012
  • Security and monitoring system has many applications and commonly used for detection, warning, alarm, etc. As the networking technology advances, user requirements are getting higher. An intelligent and cooperative surveillance system is proposed to meet current user demands and improve the performance. This paper focuses on the implementation issue for the embedded intelligent surveillance system. To cover wide area cooperative function is implemented and connected by wireless sensor network technology. Also to improve the performance lots of sensors are employed into the surveillance system to reduce the error but improve the detection probability. The proposed surveillance system is composed of vision sensor (camera), mic array sensor, PIR sensor, etc. Between the sensors, data is transferred by IEEE 802.11s or Zigbee protocol. We deployed a private network for the sensors and multiple gateways for better data throughput. The developed system is targeted to the traffic accident detection and alarm. However, its application can be easily changed to others by just changing software algorithm in a DSP chip.

A Real-time Pedestrian Detection based on AGMM and HOG for Embedded Surveillance

  • Nguyen, Thanh Binh;Nguyen, Van Tuan;Chung, Sun-Tae
    • Journal of Korea Multimedia Society
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    • v.18 no.11
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    • pp.1289-1301
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    • 2015
  • Pedestrian detection (PD) is an essential task in various applications and sliding window-based methods utilizing HOG (Histogram of Oriented Gradients) or HOG-like descriptors have been shown to be very effective for accurate PD. However, due to exhaustive search across images, PD methods based on sliding window usually require heavy computational time. In this paper, we propose a real-time PD method for embedded visual surveillance with fixed backgrounds. The proposed PD method employs HOG descriptors as many PD methods does, but utilizes selective search so that it can save processing time significantly. The proposed selective search is guided by restricting searching to candidate regions extracted from Adaptive Gaussian Mixture Model (AGMM)-based background subtraction technique. Moreover, approximate computation of HOG descriptor and implementation in fixed-point arithmetic mode contributes to reduction of processing time further. Possible accuracy degradation due to approximate computation is compensated by applying an appropriate one among three offline trained SVM classifiers according to sizes of candidate regions. The experimental results show that the proposed PD method significantly improves processing speed without noticeable accuracy degradation compared to the original HOG-based PD and HOG with cascade SVM so that it is a suitable real-time PD implementation for embedded surveillance systems.

A Design of Intelligent Surveillance System Based on Mobile Robot and Network Camera (모바일 로봇 및 네트워크 카메라 기반 지능형 감시 시스템 설계)

  • Park, Jung-Hyun;Lee, Min-Young;Sim, Kwee-Bo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.4
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    • pp.476-481
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    • 2008
  • The necessity of intelligent surveillance system is gradually considered seriously from the space where the security is important. From this paper will load Network Camera in Mobile Robot based on embedded Linux and Goal is in the system embodiment will be able to track the intruder. From Network Camera uses Wireless Lan transmits an image with server, grasps direction of the intruder used Block Matching algorithms from server, transmits direction information and tracks an intruder. The robot tracks the intruder according to gets the effective image of an intruder. In compliance with this paper the system which is embodied is linked with a different surveillance system and as intelligent surveillance system there is a possibility of becoming worse a reliability.

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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Low Complexity FMCW Surveillance Radar Algorithm Using Phase Difference of Dual Chirps (듀얼첩간 위상차이를 이용한 저복잡도 FMCW 감시 레이더 알고리즘)

  • Jin, YoungSeok;Hyun, Eugin;Kim, Sangdong;Kim, Bong-seok;Lee, Jonghun
    • IEMEK Journal of Embedded Systems and Applications
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    • v.12 no.2
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    • pp.71-77
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    • 2017
  • This paper proposes a low complexity frequency modulated continuous wave (FMCW) surveillance radar algorithm. In the conventional surveillance radar systems, the two dimensional (2D) fast Fourier transform (FFT) method is usually employed in order to detect the distance and velocity of the targets. However, in a surveillance radar systems, it is more important to immediately detect the presence or absence of the targets, rather than accurately detecting the distance or speed information of the target. In the proposed algorithm, in order to immediately detect the presence or absence of targets, 1D FFT is performed on the first and M-th bit signals among a total of M beat signals and then a phase change between two FFT outputs is observed. The range of target is estimated only when the phase change occurs. By doing so, the proposed algorithm achieves a significantly lower complexity compared to the conventional surveillance scheme using 2D FFT. In addition, show in order to verify the performance of the proposed algorithm, the simulation and the experiment results are performed using 24GHz FMCW radar module.

Location and Direction Tracking of Small UAVs on Occlusion Area in Moving Surveillance System (이동보안시스템에서 폐색영역에서의 소형무인비행체 위치 및 방향 추적)

  • Moon, Yong-Ho;Cheon, Seung-Hyeon;Ha, Seok-Wun
    • IEMEK Journal of Embedded Systems and Applications
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    • v.10 no.5
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    • pp.317-324
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    • 2015
  • In his paper, we propose the graphic-based direction tracking system that be able to detect the current location and direction of the flight object and virtually run the pointing to the flight direction when a small UAV is located in the occlusion area behind buildings or obstacles in the moving surveillance systems. Based on the experimental results about the simulation flight path extracted from the Mission Planner we found the proposed system operates the desired flight mission effectively in tracking.