• 제목/요약/키워드: Moving Detection

검색결과 1,069건 처리시간 0.031초

Edge 검출과 Optical flow 기반 이동물체의 정보 추출 (Information extraction of the moving objects based on edge detection and optical flow)

  • 장민혁;박종안
    • 한국통신학회논문지
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    • 제27권8A호
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    • pp.822-828
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    • 2002
  • 다제약 접근기반 OF(optical flow) 평가기술이 이동 물체의 인식에 자주 이용되고 있다. 그러나 OF 평가시간 뿐만 아니라 오차 문제로 인하여 사용이 제한되고 있다. 본 논문에서는 sobel 에쥐 검출과 다제약 접근기반 OF를 이용하여 효율적으로 움직임 정보를 추출하는 방법을 제안한다. 먼저 에쥐 검출 후 차영상과 영역분할기법으로 영상열 내 이동물체를 검출하고 임계치 처리로 잡음에 의해 검출된 이동물체들을 제거한다. 그리고 OF 최적 제약선을 찾기 위한 CHT와 Voting 누적을 적용한다. 이때 에쥐 검출과 영역분할을 이용함으로써 연속하는 영상열 내에서 이동 물체를 찾기 위한 CHT 계산시간을 현저히 줄이는 것이 가능하다. CHT 기반의 Voting은 최소자승법을 가미함으로써 오차 또한 감소시킨다. 그리고 제약선에 따른 수많은 점들을 계산하는 작업도 변환된 기울기-교점 파라미터를 사용함으로써 줄어들게 된다. 시뮬레이션 결과 영상 내에서 이동물체 인식비가 증가됨을 보였고 이동물체의 움직임 정보를 제공하는 OF 벡터도 매우 효율적으로 검출됨을 확인하였다.

프레임간 가우시안 잡음이 있는 동영상에서의 움직임 객체 검출 (The moving object detection for moving picture with gaussian noise)

  • 김동우;송영준;김애경;안재형
    • 한국콘텐츠학회:학술대회논문집
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    • 한국콘텐츠학회 2009년도 춘계 종합학술대회 논문집
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    • pp.839-842
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    • 2009
  • 동영상에서 움직임 검출을 위해서 가장 일반적으로 사용하는 방법은 차영상을 이용하는 방법이다. 그러나 프레임 단위의 차영상을 이용할 때 간혹 카메라, 그래버 카드, 또는 기상 조건에 따라 가우시안 잡음이 발생할 경우 이를 극복하기 위한 방법을 제안한다. 제안 방법은 움직임 검출이 사람이나 차량과 같이 객체의 크기가 큰 경우를 추출한다는 가정 아래, 차영상으로 생긴 가우시안 잡음 형태가 들어간 영상에서 형태학적 필터링 및 이진화를 동시에 수행하여 움직임 검출에 있어서 에러가 발생하는 부분을 감소시켜 대략적인 큰 물체의 움직임을 검출할 수 있음을 확인하였다. 따라서, 안개가 낀 날과 같이 차영상에서의 한계를 극복하는 대안으로서 움직임을 추정하는 곳에 사용될 수 있다.

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동적 배경에서의 고밀도 광류 기반 이동 객체 검출 (Dense Optical flow based Moving Object Detection at Dynamic Scenes)

  • 임효진;최연규;구엔 칵 쿵;정호열
    • 대한임베디드공학회논문지
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    • 제11권5호
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    • pp.277-285
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    • 2016
  • Moving object detection system has been an emerging research field in various advanced driver assistance systems (ADAS) and surveillance system. In this paper, we propose two optical flow based moving object detection methods at dynamic scenes. Both proposed methods consist of three successive steps; pre-processing, foreground segmentation, and post-processing steps. Two proposed methods have the same pre-processing and post-processing steps, but different foreground segmentation step. Pre-processing calculates mainly optical flow map of which each pixel has the amplitude of motion vector. Dense optical flows are estimated by using Farneback technique, and the amplitude of the motion normalized into the range from 0 to 255 is assigned to each pixel of optical flow map. In the foreground segmentation step, moving object and background are classified by using the optical flow map. Here, we proposed two algorithms. One is Gaussian mixture model (GMM) based background subtraction, which is applied on optical map. Another is adaptive thresholding based foreground segmentation, which classifies each pixel into object and background by updating threshold value column by column. Through the simulations, we show that both optical flow based methods can achieve good enough object detection performances in dynamic scenes.

A Study on Quick Detection of Variance Change Point of Time Series under Harsh Conditions

  • Choi, Hyun-Seok;Choi, Sung-Hwan;Kim, Tae-Yoon
    • Journal of the Korean Data and Information Science Society
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    • 제17권4호
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    • pp.1091-1098
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    • 2006
  • Park et al.(2005) and Choi et al.(2006) studied quick detection of variance change point for time series data in progress. For efficient detection they used moving variance ratio equipped with two tuning parameters; information tuning parameter p and lag tuning parameter q. In this paper, the moving variance ratio is studied under harsh conditions.

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Surf points based Moving Target Detection and Long-term Tracking in Aerial Videos

  • Zhu, Juan-juan;Sun, Wei;Guo, Bao-long;Li, Cheng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권11호
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    • pp.5624-5638
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    • 2016
  • A novel method based on Surf points is proposed to detect and lock-track single ground target in aerial videos. Videos captured by moving cameras contain complex motions, which bring difficulty in moving object detection. Our approach contains three parts: moving target template detection, search area estimation and target tracking. Global motion estimation and compensation are first made by grids-sampling Surf points selecting and matching. And then, the single ground target is detected by joint spatial-temporal information processing. The temporal process is made by calculating difference between compensated reference and current image and the spatial process is implementing morphological operations and adaptive binarization. The second part improves KALMAN filter with surf points scale information to predict target position and search area adaptively. Lastly, the local Surf points of target template are matched in this search region to realize target tracking. The long-term tracking is updated following target scaling, occlusion and large deformation. Experimental results show that the algorithm can correctly detect small moving target in dynamic scenes with complex motions. It is robust to vehicle dithering and target scale changing, rotation, especially partial occlusion or temporal complete occlusion. Comparing with traditional algorithms, our method enables real time operation, processing $520{\times}390$ frames at around 15fps.

Performance of Seamless Handoff Scheme with Fast Moving Detection

  • Kim Dong Ok;Yoon Hong;Yoon Chong Hoo
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2004년도 학술대회지
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    • pp.588-591
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    • 2004
  • This paper describes a new approach to Internet host mobility. We argue that local mobility, the performance of existing mobile host protocol can be significantly improved. It proposes Fast Moving Detection scheme that based on neighbor AP channel information and moving detection table. And, it composes Local Area Clustering Path (LACP) domain that collected in AP's channel information and MN interface information. It stored the roaming table to include channel information and moving detection. Those which use the proposal scheme will need to put LACP information into the beacon or probe frame. Each AP uses scheme to inform available channel information to MN. From the simulation result, we show that the proposed scheme is advantageous over the legacy schemes in terms of the burst blocking probability and the link utilization.

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열펌프의 고장진단시스템 구축을 위한 정상상태 진단기 개발 (Development of a Real-Time Steady State Detector of a Heat Pump System to Develop Fault Detection and Diagnosis System)

  • 김민성;윤석호;김민수
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2008년도 추계학술대회B
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    • pp.2070-2075
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    • 2008
  • Identification of steady-state is the first step in developing a fault detection and diagnosis (FDD) system. In a complete FDD system, the steady-state detector will be included as a module in a self-learning algorithm which enables the working system's reference model to "tune" itself to its particular installation. In this study, a steady-state detector of a residential air conditioner based on moving windows was designed. Seven representing measurements were selected as key features for steady-state detection. The optimized moving window size and the feature thresholds was suggested through startup transient test and no-fault steady-state test. Performance of the steady-state detector was verified during indoor load change test. From the research, the general methodology to design a moving window steady-state detector was provided for vapor compression applications.

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Multiple Properties-Based Moving Object Detection Algorithm

  • Zhou, Changjian;Xing, Jinge;Liu, Haibo
    • Journal of Information Processing Systems
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    • 제17권1호
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    • pp.124-135
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    • 2021
  • Object detection is a fundamental yet challenging task in computer vision that plays an important role in object recognition, tracking, scene analysis and understanding. This paper aims to propose a multiproperty fusion algorithm for moving object detection. First, we build a scale-invariant feature transform (SIFT) vector field and analyze vectors in the SIFT vector field to divide vectors in the SIFT vector field into different classes. Second, the distance of each class is calculated by dispersion analysis. Next, the target and contour can be extracted, and then we segment the different images, reversal process and carry on morphological processing, the moving objects can be detected. The experimental results have good stability, accuracy and efficiency.

Identification of beam crack using the dynamic response of a moving spring-mass unit

  • An, Ning;Xia, He;Zhan, Jiawang
    • Interaction and multiscale mechanics
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    • 제3권4호
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    • pp.321-331
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    • 2010
  • A new technique is proposed for bridge structural damage detection based on spatial wavelet analysis of the time history obtained from vehicle body moving over the bridge, which is different from traditional detection techniques based on the bridge response. A simply-supported Bernoulli-Euler beam subjected to a moving spring-mass unit is established, with the crack in the beam simulated by modeling the cracked section as a rotational spring connecting two undamaged beam segments, and the equations of motion for the system is derived. By using the transfer matrix method, the natural frequencies and mode shapes of the cracked beam are determined. The responses of the beam and the moving spring-mass unit are obtained by modal decomposition theory. The continuous wavelet transform is calculated on the displacement time histories of the sprung-mass. The case study result shows that the damage location can be accurately determined and the method is effective.

이동카메라에서 이동물체 감지를 위한 배경에지 생성에 관한 연구 (A Study of Background Edge Generation for Moving Object Detection under Moving Camera)

  • 이준형;채옥삼
    • 한국컴퓨터정보학회논문지
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    • 제11권6호
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    • pp.151-156
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    • 2006
  • 본 논문에서는 이동 카메라를 이용하여 얻은 영상에서 이동 물체 자동 검출 알고리즘을 위한 배경 에지 생성을 제시한다. 배경 영상은 삼각대 위에 고정시킨 카메라를 수평방향으로 회전하여 얻은 영상을 정렬시켜 재구성하여 만든다. 입력영상과 배경영상간의 에지 매칭 방법과 함께 강건한 파노라믹 배경 에지 생성을 위한 효율적인 방법을 제시한다. 제안한 알고리즘은 실제 영상 열에 적용하였다. 제안된 방법은 비디오 감시는 물론 침입자 검출과 같은 여러 감시 시스템에 성공적으로 이용될 수 있다.

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