• Title/Summary/Keyword: Motion Detection

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Implementation of Effective Automatic Foreground Motion Detection Using Color Information

  • Kim, Hyung-Hoon;Cho, Jeong-Ran
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.6
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    • pp.131-140
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    • 2017
  • As video equipments such as CCTV are used for various purposes in fields of society, digital video data processing technology such as automatic motion detection is essential. In this paper, we proposed and implemented a more stable and accurate motion detection system based on background subtraction technique. We could improve the accuracy and stability of motion detection over existing methods by efficiently processing color information of digital image data. We divided the procedure of color information processing into each components of color information : brightness component, color component of color information and merge them. We can process each component's characteristics with maximum consideration. Our color information processing provides more efficient color information in motion detection than the existing methods. We improved the success rate of motion detection by our background update process that analyzed the characteristics of the moving background in the natural environment and reflected it to the background image.

Recent Trends in Human Motion Detection Technology and Flexible/stretchable Physical Sensors: A Review

  • Park, Inkyu
    • Journal of Sensor Science and Technology
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    • v.26 no.6
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    • pp.391-396
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    • 2017
  • Human body motion detection is important in several industry sectors, such as entertainment, healthcare, rehabilitation, and so on. In this paper, we first discuss commercial human motion detection technologies (optical markers, MEMS acceleration sensors, infrared imaging, etc.) and then explain recent advances in the development of flexible and stretchable strain sensors for human motion detection. In particular, flexible and stretchable strain sensors that are fabricated using carbon nanotubes, silver nanowires, graphene, and other materials are reviewed.

Motion Detection Using Electric Field Theory

  • Ono, Naoki;Yang, Yee-Hong
    • Proceedings of the IEEK Conference
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    • pp.823-826
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    • 2000
  • Motion detection is an important step in computer vision and image processing. Traditional motion detection systems are classified into two categories, namely, feature based and gradient based. In feature based motion detection, features in consecutive frames are detected and matched. Gradient based methods assume that the intensity varies linearly and locally. The method, which we propose, is neither feature nor gradient based but uses the electric field theory. The pixels in an image are modeled as point charges and motion is detected by using the variations between the two electric fields produced by the charges corresponding to the two images.

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Unusual Motion Detection for Vision-Based Driver Assistance

  • Fu, Li-Hua;Wu, Wei-Dong;Zhang, Yu;Klette, Reinhard
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.15 no.1
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    • pp.27-34
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    • 2015
  • For a vision-based driver assistance system, unusual motion detection is one of the important means of preventing accidents. In this paper, we propose a real-time unusual-motion-detection model, which contains two stages: salient region detection and unusual motion detection. In the salient-region-detection stage, we present an improved temporal attention model. In the unusual-motion-detection stage, three kinds of factors, the speed, the motion direction, and the distance, are extracted for detecting unusual motion. A series of experimental results demonstrates the proposed method and shows the feasibility of the proposed model.

Environment Implementation of Real-time Supervisory System Using Motion Detection Method (동작 검출 기법을 이용한 실시간 감시시스템의 구현)

  • 김형균;고석만;오무송
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • pp.999-1002
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    • 2003
  • In this study, embodied supervisory system that apply motion detection technique to small web camera and detects watch picture. Motion detection technique that use pixel value of car image that use in existing need memory to store background image. Also, there is sensitive shortcoming at increase of execution time by data process of pixel unit and noise. Suggested technique that compare extracting motion information by block unit to do to have complexion that solve this shortcoming and is strong at noise. Because motion information by block compares block characteristic value of image without need frame memory, store characteristic cost by block of image. Also, can get effect that reduce influence about noise and is less sensitive to flicker etc.. of camera more than motion detection that use pixel value in process that find characteristic value by block unit.

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MOTION DETECTION USING CURVATURE MAP AND TWO-STEP BIMODAL SEGMENTATION

  • Lee, Suk-Ho
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.13 no.4
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    • pp.247-256
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    • 2009
  • In this paper, a motion detection algorithm which works well in low illumination environment is proposed. By using the level set based bimodal motion segmentation, the algorithm obtains an automatic segmentation of the motion region and the spurious regions due to the large CCD noise in low illumination environment are removed effectively.

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Effective Automatic Foreground Motion Detection Using the Statistic Information of Background

  • Kim, Hyung-Hoon;Cho, Jeong-Ran
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.9
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    • pp.121-128
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    • 2015
  • In this paper, we proposed and implemented the effective automatic foreground motion detection algorithm that detect the foreground motion by analyzing the digital video data that captured by the network camera. We classified the background as moving background, fixed background and normal background based on the standard deviation of background and used it to detect the foreground motion. According to the result of experiment, our algorithm decreased the fault detection of the moving background and increased the accuracy of the foreground motion detection. Also it could extract foreground more exactly by using the statistic information of background in the phase of our foreground extraction.

Sleep Mode Detection for Smart TV using Face and Motion Detection

  • Lee, Suwon;Seo, Yong-Ho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.7
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    • pp.3322-3337
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    • 2018
  • Sleep mode detection is a significant power management and green computing feature. However, it is difficult for televisions and smart TVs to detect deactivation events because we can use these devices without the assistance of an input device. In this paper, we propose a robust method for smart TVs to detect deactivation events based on a visual combination of face and motion detection. The results of experiments conducted indicate that the proposed method significantly reduces incorrect face detection and human absence by means of motion detection. The results also show that the proposed method is robust and effective for smart TVs to reduce power consumption.

Camera Motion Detection Using Estimation of Motion Vector's Angle (모션 벡터의 각도 성분 추정을 통한 카메라 움직임 검출)

  • Kim, Jae Ho;Lee, Jang Hoon;Jang, Soeun
    • Journal of Korea Multimedia Society
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    • v.21 no.9
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    • pp.1052-1061
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    • 2018
  • In this paper, we propose a new algorithm that is robust against the effects of objects that are relatively unaffected by camera motion and can accurately detect camera motion even in high resolution images. First, for more accurate camera motion detection, a global motion filter based on entropy of a motion vector is used to distinguish the background and the object. A block matching algorithm is used to find exact motion vectors. In addition, a matched filter with the angle of the ideal motion vector of each block is used. Motion vectors including 4 kinds of diagonal direction, zoom in, and zoom out are added additionally. The experiment shows that the precision, recall, and accuracy of camera motion detection compared to the recent results is improved by 12.5%, 8.6% and 9.5%, respectively.

A Block-based Motion Detection Algorithm with Adaptive Thresholds for Digital Video Surveillance Systems (적응적으로 임계값을 결정하는 블럭 기반의 디지털 감시 시스템용 움직임 검출 알고리즘)

  • Yang, Yun-Seok;Lee, Dong-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.37 no.5
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    • pp.31-41
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    • 2000
  • This paper proposes a block-based motion detection algorithm for digital video surveillance system which adaptively decides the threshold according to the kinds of images We first compute the features of a block after dividing each Image into small sub-block regions, and analyze performance of the motion detection algorithm based on statistic features by using the proposed threshold-decision method. Motion vectors are used to analyze motion degree and adaptively determine the threshold The simulation results show the performances of motion detection algorithms according to sub-block size, statistic features, noise, and threshold.

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