• 제목/요약/키워드: Neighborhood Tracking

검색결과 25건 처리시간 0.018초

다변수 비선형시스템에서의 강인한 추적 (Robust tracking in multivariable nonlinear systems)

  • 백운보;배종일;이만형
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
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    • pp.451-456
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    • 1990
  • We treat the problem of the robust tracking of a class of nonlinear systems which can be asymptotically decoupled in approximate sense by state variable feedback. A nonlinear control law is derived such that the tracking error in the closed loop system is uniformly bounded and tends to a certain small neighborhood of the origin. Simulation results show that simultaneous lateral and longitudinal maneuvers in airplane can be accurately performed in spite of uncertainty in stability derivatives.

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PSN 픽터의 해석 및 추적성능 예측 ((Theoretical Analysis and Performance Prediction for PSN Filter Tracking))

  • 정영헌;김동현;홍순목
    • 전자공학회논문지SC
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    • 제39권2호
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    • pp.166-175
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    • 2002
  • 이 논문에서는 표적 추적에 사용되는 PSN(Probabilistic Strongest Neighbor) 필터의 추적 성능을 예측한다. PSN 필터는 가장 강한 신호 크기를 가진 측정이 표적이외의 것으로부터 발생할 수 있다는 사건을 충분히 고려하기 때문에, 추적 성능에서 뿐만 아니라, 계산량 측면에서도 PDA(Probabilistic Data association) 필터보다 뛰어나다고 알려져 있다. 추적필터의 추정오차 공분산행렬(covariance matrix)은 추적의 성능을 결정하는 성능지수(performance index)로 널리 사용된다. PSN 필터의 추정오차 공분산행렬은 측정 데이터의 함수로써, 측정 데이터와 무관하게 추적기의 성능을 표현하기 위해서 HYCA(HYbrid Conditional Average)방법을 이용하여 추정오차 공분산행렬의 기대값에 대한 식을 제시하였다. 수치실험을 통하여 이 논문에서 제시한 성능 예측이 타당함을 보인다.

계층적인 메쉬 구조를 이용한 영상분할 방법 (Image Segmentation Using Hierarchical Meshes)

  • 임동근;호요성
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 1999년도 학술대회
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    • pp.9-14
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    • 1999
  • The object boundary of an image plays an important role for image interpretation. In this paper, we introduce a concept of hierarchical mesh-based image segmentation for finding object boundaries. In each hierarchical layer, we employ neighborhood searching and boundary tracking methods to refine the initial boundary estimate. We also apply a local region growing method to define closed contours. Experimental results indicate that reliable segmentation of objects can be accomplished by the pro-posed tow complexity technique.

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고속 정합법에 의한 실시간 자동목표 추정 (Real-time Automatic Target Tracking Based on a Fast Matching Method)

  • 김세환;김남철
    • 대한전자공학회논문지
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    • 제25권1호
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    • pp.63-71
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    • 1988
  • In this paper, a fast matching method using hierarchical neighborhood search and subtemplate to reduce very heavy computational load of the conventional matching method, is presented. Some parameters of the proposed method are chosen so that an automatic target tracker to which it is applied can track one moving object well in comparatively simple background. Experimental results show that its performance is not so degraded in spite of high computational reduction over that of the matching method using 3-step search.

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A Simple Stable Method in Real-time Lane Tracking of Broken Lanes

  • 쉬수단;최요한;김권;이창우
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2007년도 가을 학술발표논문집 Vol.34 No.2 (A)
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    • pp.229-230
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    • 2007
  • Lane detection is one of the major components of traffic intelligence. It is impossible to recognize lanes as human do in all kinds of special situations; however, we can try to solve special problems with special methods. In this paper we propose a simple method using color segmentation, the Probabilistic Hough Transform (PHT), and the Least-Square in real-time lane tracking. Vehicles in neighborhood can be eliminated with one simple threshold in segmentation. Meanwhile, broken shape lanes in different road conditions can be successfully detected using the combination of PHT and Least-Square method. Eventually, this method is tested with groups of static images downloaded from internet and video sequences shot randomly on some highways. Satisfactory results are received.

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일방향 순차층위 스네이크 모델에 의한 디지털영상의 특징점 추적 (Feature Points Tracking of Digital Image By One-Directional Iterating Layer Snake Model)

  • 황중원;황재호
    • 대한전자공학회논문지SP
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    • 제44권4호통권316호
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    • pp.86-92
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    • 2007
  • 2D 영상의 특징점을 추적하는 이산동적 모델을 고안한다. 종래의 스네이크 접근은 내외 추진력으로 구성된 에너지함수를 최소화하도록 구획을 변형시켜가면서 영상 내의 원하는 특징에 밀착시켜간다. 이 때 스네이크화소를 중심한 인접화소군은 사각형 같은 평면 2차 행렬이다. 본 논문에서는 유사 특성점들을 상호 연결하는 모델 구조를 제시한다. 에너지모델은 그 국부최소점이 활성처리에 유용한 교차 해법에 적합하도록 설계한다. 추적시 선 형태의 1차 행렬 블록을 사용한다. 진행 방향의 반대 끝 라인으로부터 굴곡상태를 만족하는 시발점들을 선정하고 에너지 최소처리를 통해 이웃 라인으로 순차 자동 이동한다. 추적 경로는 상승 하강점 또는 극대 극소점과 같은 굴곡 한계에 의존한다. 이와 같은 층위적 접근은 인접데이터 라인 사이에 수직 또는 수평 방향으로 높은 상관성을 갖는 일방향 특성이 있는 디지털 영상의 특징점 추적에 유용하다. 그리고 인체 경동맥초음파영상에서 그 내 외막 시점을 추적하는 실험으로 알고리즘의 효과를 확인하였다.

표적 탐지/추적 성능 향상을 위한 불균일 미세 잡음 영상 화질개선 연구 (A study on enhancement of heterogeneous noisy image quality for the performance improvement of target detection and tracking)

  • 김용;유필훈;김다솔
    • 한국멀티미디어학회논문지
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    • 제17권8호
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    • pp.923-936
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    • 2014
  • Images can be contaminated with different types of noise, for different reasons. The neighborhood averaging and smoothing by image averaging are the classical image processing techniques for noise removal. The classical spatial filtering refers to the aggregate of pixels composing an image and operating directly on these pixels. To reduce or remove effectively noise in image sequences, it usually needs to use noise reduction filter based on space or time domain such as method of spatial or temporal filter. However, the method of spatial filter can generally cause that signals of objects as the target are also blurred. In this paper, we propose temporal filter using the piece-wise quadratic function model and enhancement algorithm of image quality for the performance improvement of target detection and tracking by heterogeneous noise reduction. Image tracking simulation that utilizes real IIR(Imaging Infra-Red) images is employed to evaluate the performance of the proposed image processing algorithm.

Snake 모델을 이용한 다중 이동 객체 검출 및 추적 (Multiple Moving Objects Detection and Tracking Using Snake Model)

  • 우장명;김성동;최기호
    • 한국ITS학회 논문지
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    • 제2권2호
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    • pp.85-95
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    • 2003
  • 본 논문은 Snake 모델을 이용하여 동영상에서 주위 환경 변화에 적응 가능한 다중 이동 객체 추적 시스템을 제안하였다. Snake 모델은 배경이 복잡한 영상에 대해선 객체의 윤곽선을 정확히 표현하지 못하므로 영상분할 시 초기 위치에 따라 민감하게 영향을 받는다. 제안된 시스템은 프레임간의 차(difference)영상을 이용하여 배경영상을 획득하고, 픽셀의 인접성을 조사하여 객체를 분할하고 위치 특징 값을 구하며, 분할된 특징 값들을 Snake모델의 초기 위치 값으로 부여함으로써 초기 위치 값에 민감한 Snake 모델을 개선하였다 또한 본 시스템은 복잡한 배경 영상을 단순화하고, Snake를 이루는 각 정점들을 객체의 위치로 놓이게 함으로써 탐색 공간을 줄였다. 30fps로 저장된 AVI파일을 적용함으로써 다중 이동차량 추적 시스템으로의 응용 가능함을 보였다.

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Combining Model-based and Heuristic Techniques for Fast Tracking the Global Maximum Power Point of a Photovoltaic String

  • Shi, Ji-Ying;Xue, Fei;Ling, Le-Tao;Li, Xiao-Fei;Qin, Zi-Jian;Li, Ya-Jing;Yang, Ting
    • Journal of Power Electronics
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    • 제17권2호
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    • pp.476-489
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    • 2017
  • Under partial shading conditions (PSCs), multiple maximums may be exhibited on the P-U curve of string inverter photovoltaic (PV) systems. Under such conditions, heuristic methods are invalid for extracting a global maximum power point (GMPP); intelligent algorithms are time-consuming; and model-based methods are complex and costly. To overcome these shortcomings, a novel hybrid MPPT (MPF-IP&O) based on a model-based peak forecasting (MPF) method and an improved perturbation and observation (IP&O) method is proposed. The MPF considers the influence of temperature and does not require solar radiation measurements. In addition, it can forecast all of the peak values of the PV string without complex computation under PSCs, and it can determine the candidate GMPP after a comparison. Hence, the MPF narrows the searching range tremendously and accelerates the convergence to the GMPP. Additionally, the IP&O with a successive approximation strategy searches for the real GMPP in the neighborhood of the candidate one, which can significantly enhance the tracking efficiency. Finally, simulation and experiment results show that the proposed method has a higher tracking speed and accuracy than the perturbation and observation (P&O) and particle swarm optimization (PSO) methods under PSCs.

A Disctete Model Reference Control With a Neural Network System Ldentification for an Active Four Wheel Steering System

  • 김호용;최창환
    • 한국지능시스템학회논문지
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    • 제7권4호
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    • pp.29-39
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    • 1997
  • A discrete model reference control scheme for a vehicle four wheel steering system(4WS) is proposed and evaluated for a class of discrete time nonlinar dynamics. The schmen employs a neural network to identify the plan systems, wher the neural network estimates the nonlinear dynamics of the plant. The algorithm is proven to be globally stable, with tracking errors converging to the neighborhood of zero. The merits of this scheme is that the global system stability is guaranteed. Whith thd resulting identification model which contains the neural networks, the parameters of controller are adjusted. The proposed scheme is applied to the vehicle active four wheel system and shows the validity and effectiveness through simulation. The three-degree-of freedom vehicle handling model is used to investigate vehicle handing performances. In simulation of the J-turn maneuver, the yaw rate overshoot reduction of a typical mid-size car is improved by 30% compared to a two wheel steering system(2WS) case, resulting that the proposed scheme gives faster yaw rate response andl smaller side slip angle than the 2WS case.

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