• Title, Summary, Keyword: Motion Detection

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Fire Detection Algorithm for a Quad-rotor using Ego-motion Compensation (Ego-Motion 보정기법을 적용한 쿼드로터의 화재 감지 알고리즘)

  • Lee, Young-Wan;Kim, Jin-Hwang;Oh, Jeong-Ju;Kim, Hakil
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.1
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    • pp.21-27
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    • 2015
  • A conventional fire detection has been developed based on images captured from a fixed camera. However, It is difficult to apply current algorithms to a flying Quad-rotor to detect fire. To solve this problem, we propose that the fire detection algorithm can be modified for Quad-rotor using Ego-motion compensation. The proposed fire detection algorithm consists of color detection, motion detection, and fire determination using a randomness test. Color detection and randomness test are adapted similarly from an existing algorithm. However, Ego-motion compensation is adapted on motion detection for compensating the degree of Quad-rotor's motion using Planar Projective Transformation based on Optical Flow, RANSAC Algorithm, and Homography. By adapting Ego-motion compensation on the motion detection step, it has been proven that the proposed algorithm has been able to detect fires 83% of the time in hovering mode.

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.

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.

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.

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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A Motion Detection Approach based on UAV Image Sequence

  • Cui, Hong-Xia;Wang, Ya-Qi;Zhang, FangFei;Li, TingTing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.3
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    • pp.1224-1242
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    • 2018
  • Aiming at motion analysis and compensation, it is essential to conduct motion detection with images. However, motion detection and tracking from low-altitude images obtained from an unmanned aerial system may pose many challenges due to degraded image quality caused by platform motion, image instability and illumination fluctuation. This research tackles these challenges by proposing a modified joint transform correlation algorithm which includes two preprocessing strategies. In spatial domain, a modified fuzzy edge detection method is proposed for preprocessing the input images. In frequency domain, to eliminate the disturbance of self-correlation items, the cross-correlation items are extracted from joint power spectrum output plane. The effectiveness and accuracy of the algorithm has been tested and evaluated by both simulation and real datasets in this research. The simulation experiments show that the proposed approach can derive satisfactory peaks of cross-correlation and achieve detection accuracy of displacement vectors with no more than 0.03pixel for image pairs with displacement smaller than 20pixels, when addition of image motion blurring in the range of 0~10pixel and 0.002variance of additive Gaussian noise. Moreover,this paper proposes quantitative analysis approach using tri-image pairs from real datasets and the experimental results show that detection accuracy can be achieved with sub-pixel level even if the sampling frequency can only attain 50 frames per second.

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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The motion estimation algorithm implemented by the color / shape information of the object in the real-time image (실시간 영상에서 물체의 색/모양 정보를 이용한 움직임 검출 알고리즘 구현)

  • Kim, Nam-Woo;Hur, Chang-Wu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.11
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    • pp.2733-2737
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    • 2014
  • Motion detection according to the movement and the change area detection method according to the background difference and the motion history image for use in a motion estimation technique using a real-time image, the motion detection method according to the optical flow, the back-projection of the histogram of the object to track for motion tracking At the heart of MeanShift center point of the object and the object to track, while used, the size, and the like due to the motion tracking algorithm CamShift, Kalman filter to track with direction. In this paper, we implemented the motion detection algorithm based on color and shape information of the object and verify.

AUTOMATIC MOTION DETECTION USING FALSE BACKGROUND ELIMINATION

  • Seo, Jin Keun;Lee, Sukho
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.17 no.1
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    • pp.47-54
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    • 2013
  • This work deals with automatic motion detection for with surveillance tracking that aims to provide high-lighting movable objects which is discriminated from moving backgrounds such as moving trees, etc. For this aim, we perform a false background region detection together with an initial foreground detection. The false background detection detects the moving backgrounds, which become eliminated from the initial foreground detection. This false background detection is done by performing the bimodal segmentation on a deformed image, which is constructed using the information of the dominant colors in the background.