• Title/Summary/Keyword: Visual surveillance

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A Fast and Precise Blob Detection

  • Nguyen, Thanh Binh;Chung, Sun-Tae
    • Proceedings of the Korea Contents Association Conference
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    • 2009.05a
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    • pp.23-29
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    • 2009
  • Blob detection is an essential ingredient process in some computer applications such as intelligent visual surveillance. However, previous blob detection algorithms are still computationally heavy so that supporting real-time multi-channel intelligent visual surveillance in a workstation or even one-channel real-time visual surveillance in a embedded system using them turns out prohibitively difficult. In this paper, we propose a fast and precise blob detection algorithm for visual surveillance. Blob detection in visual surveillance goes through several processing steps: foreground mask extraction, foreground mask correction, and connected component labeling. Foreground mask correction necessary for a precise detection is usually accomplished using morphological operations like opening and closing. Morphological operations are computationally expensive and moreover, they are difficult to run in parallel with connected component labeling routine since they need much different processing from what connected component labeling does. In this paper, we first develop a fast and precise foreground mask correction method utilizing on neighbor pixel checking which is also employed in connected component labeling so that the developed foreground mask correction method can be incorporated into connected component labeling routine. Through experiments, it is verified that our proposed blob detection algorithm based on the foreground mask correction method developed in this paper shows better processing speed and more precise blob detection.

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Design of Visual Surveillance System based on Wireless High Definition Image Transmission Technology (무선 고해상도 영상 전송 기술에 기반한 영상 감시 시스템의 설계)

  • Kim, Won
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.12 no.5
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    • pp.25-30
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    • 2012
  • It is important to detect dangerous objects which are intentionally abandoned in public places. Nowadays visual surveillance system is required to enhance the performance in two ways : high resolution and wireless linking ability. In this study the design of visual surveillance system is newly proposed to detect abandoned objects for social security purpose based on wireless high resolution image transmission technology. Also, to enhance PED, PAT performance, the tracking algorithm is included in the previous visual surveillance software scheme. By implementing proposed design scheme on the real wireless high resolution image transmission system, the effectiveness of the overall system is shown with the transmission performance of 4.0 Gbps speed.

An Effective Moving Cast Shadow Removal in Gray Level Video for Intelligent Visual Surveillance (지능 영상 감시를 위한 흑백 영상 데이터에서의 효과적인 이동 투영 음영 제거)

  • Nguyen, Thanh Binh;Chung, Sun-Tae;Cho, Seongwon
    • Journal of Korea Multimedia Society
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    • v.17 no.4
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    • pp.420-432
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    • 2014
  • In detection of moving objects from video sequences, an essential process for intelligent visual surveillance, the cast shadows accompanying moving objects are different from background so that they may be easily extracted as foreground object blobs, which causes errors in localization, segmentation, tracking and classification of objects. Most of the previous research results about moving cast shadow detection and removal usually utilize color information about objects and scenes. In this paper, we proposes a novel cast shadow removal method of moving objects in gray level video data for visual surveillance application. The proposed method utilizes observations about edge patterns in the shadow region in the current frame and the corresponding region in the background scene, and applies Laplacian edge detector to the blob regions in the current frame and the corresponding regions in the background scene. Then, the product of the outcomes of application determines moving object blob pixels from the blob pixels in the foreground mask. The minimal rectangle regions containing all blob pixles classified as moving object pixels are extracted. The proposed method is simple but turns out practically very effective for Adative Gaussian Mixture Model-based object detection of intelligent visual surveillance applications, which is verified through experiments.

Event recognition of entering and exiting (출입 이벤트 인식)

  • Cui, Yaohuan;Lee, Chang-Woo
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2008.06a
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    • pp.199-204
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    • 2008
  • Visual surveillance is an active topic recently in Computer Vision. Event detection and recognition is one important and useful application of visual surveillance system. In this paper, we propose a new method to recognize the entering and exiting events based on the human's movement feature and the door's state. Without sensors, the proposed approach is based on novel and simple vision method as a combination of edge detection, motion history image and geometrical characteristic of the human shape. The proposed method includes several applications such as access control in visual surveillance and computer vision fields.

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Evaluation of Application of Possibility of Visual Surveillance System for Cow Heat Detection

  • Park, Heesu;Roy, Pantu Kumar;Noh, Youngju;Park, Hyuk;Lee, Joongho;Shin, Sangtae;Cho, Jongki
    • Journal of Embryo Transfer
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    • v.31 no.2
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    • pp.137-143
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    • 2016
  • This study was conducted to evaluate a visual surveillance system. The advancement of recording technology and network service make it easy to record and transfer the videos. Moreover, progressed recognition technology help to make a distinction each other. Cows show distinguishing behaviors during their estrus period. The mounting is one of the behaviors. The result was different depending on the breed of the cows and the size of the farm. In the case of Korean native cattle, the estrus detection rate was 71.15%, however, dairy cows, the estrus detection rate was 39.38%. At the farms having below 6 modules, the estrus detection rate was 87.41%. On the other hand, at the farms having over 6 modules, the estrus detection rate was 77.78%. With the proper progress, the visual surveillance system can be used to detect heat detection.

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.

Development of Active Stereo Surveillance System with the Human-like Visual Selective Attention (인체의 상향식 선택적 주의 집중 시각 기능을 모방한 능동 스테레오 감시 시스템의 개발)

  • Jung, Bum-Soo;Lee, Min-Ho
    • Journal of Sensor Science and Technology
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    • v.13 no.2
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    • pp.144-151
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    • 2004
  • In this paper, we propose an active stereo surveillance system with human-like convergence function. The proposed system uses a bottom-up saliency map model with the human-like selective attention visual function to select an interesting region in each camera. and this system compares the landmarks whether the selective region in each camera finds a same region. If the left and right cameras successfully find a same landmarks, the implemented vision system focuses on the landmark. Using the motor encoder information, we can automatically obtain the depth information and resultantly construct a depth map using the depth information. Computer simulation and experimental results show that the proposed convergence method is very effective to implement the active stereo surveillance system.

Implementation of a Robust Visual Surveillance System for the Variation of Illumination Lights (조명광 변화에 강인한 영상 감시시스템 구현)

  • Jung, Yong-Bae;Kim, Jung-Hyeon;Kim, Tae-Hyo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.3
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    • pp.517-525
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    • 2006
  • In this paper, the algorithm which improve the efficiency of surveillance in spite of the change of light is proposed and confirmed by virtue of the experiments. One of the problems for the implementation of visual surveillance system is the image processing technique to overcome with the variations of illumination lights. Some conventional systems are generally not considered the error due to the change of lights because the system use at indoor. In practical, the factors of bad image can be classified to the ghosts due to the reflection of lights and shadows in a scene. Especially weak images and noises at night are decreased the performance of visual surveillance system. In the paper, the filter which improve the images with some change of illumination lights is designed and the gabor filter is used for recognition and tracking of the moving objects. In the results, the system showed that the recognition and tracking were obtained $92\sim100%$ of recognition rate at daytime, but $80\sim90%$ of nighttime.

Implementation of a Robust Visual Surveillance Algorithm under outdoor environment (옥외 환경에강인한 영상 감시알고리듬구현)

  • Jung, Yong-Bae;Kim, Tea-Hyo
    • Journal of the Institute of Convergence Signal Processing
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    • v.10 no.2
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    • pp.112-119
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    • 2009
  • This paper describes a robust visual surveillance algorithm under outdoor environment. One of the difficult problems for outdoor is to obtain effective updating process of background images. Because background images generally contain the shadows of buildings, trees, moving clouds and other objects, they are changed by lapse of time and variation of illumination. They provide the lowering of performance for surveillance system under outdoor. In this paper, a robust algorithm for visual surveillance system under outdoor is proposed, which apply the mixture Gaussian filter and color invariant property on pixel level to update background images. In results, it was showed that the moving objects can be detected on various shadows under outdoor.

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Real-time Human Detection under Omni-dir ectional Camera based on CNN with Unified Detection and AGMM for Visual Surveillance

  • Nguyen, Thanh Binh;Nguyen, Van Tuan;Chung, Sun-Tae;Cho, Seongwon
    • Journal of Korea Multimedia Society
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    • v.19 no.8
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    • pp.1345-1360
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    • 2016
  • In this paper, we propose a new real-time human detection under omni-directional cameras for visual surveillance purpose, based on CNN with unified detection and AGMM. Compared to CNN-based state-of-the-art object detection methods. YOLO model-based object detection method boasts of very fast object detection, but with less accuracy. The proposed method adapts the unified detecting CNN of YOLO model so as to be intensified by the additional foreground contextual information obtained from pre-stage AGMM. Increased computational time incurred by additional AGMM processing is compensated by speed-up gain obtained from utilizing 2-D input data consisting of grey-level image data and foreground context information instead of 3-D color input data. Through various experiments, it is shown that the proposed method performs better with respect to accuracy and more robust to environment changes than YOLO model-based human detection method, but with the similar processing speeds to that of YOLO model-based one. Thus, it can be successfully employed for embedded surveillance application.