• 한국정밀공학회지
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• 제15권7호
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• pp.175-181
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• 1998

This paper describes realtime visual tracking system of moving object for three dimensional target using EKF(Extended Kalman Filter). We present a new realtime visual tracking using EKF algorithm and image prediction algorithm. We demonstrate the performance of these tracking algorithm through real experiment. The experimental results show the effectiveness of the EKF algorithm and image prediction algorithm for realtime tracking and estimated state value of filter, predicting the position of moving object to minimize an image processing area, and by reducing the effect by quantization noise of image.

• 대한기계학회논문집A
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• 제27권5호
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• pp.697-704
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• 2003

In this paper, the visual tracking system for arbitrary shaped moving object is proposed. The established tracking system can be divided into model based method that needs previous model for target object and image based method that uses image feature. In the model based method, the reliable tracking is possible, but simplification of the shape is necessary and the application is restricted to definite target mod el. On the other hand, in the image based method, the process speed can be increased, but the shape information is lost and the tracking system is sensitive to image noise. The proposed tracking system is composed of the extraction process that recognizes the existence of moving object and tracking process that extracts dynamic characteristics and shape information of the target objects. Specially, active contour model is used to effectively track the object that is undergoing shape change. In initializatio n process of the contour model, the semi-automatic operation can be avoided and the convergence speed of the contour can be increased by the proposed effective initialization method. Also, for the efficient solution of the correspondence problem in multiple objects tracking, the variation function that uses the variation of position structure in image frame and snake energy level is proposed. In order to verify the validity and effectiveness of the proposed tracking system, real time tracking experiment for multiple moving objects is implemented.

• 한국컴퓨터정보학회논문지
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• 제22권5호
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• pp.21-28
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• 2017

As technology related to digital imaging equipment is developed and generalized, digital imaging system is used for various purposes in fields of society. The object tracking technology from digital image data in real time is one of the core technologies required in various fields such as security system and robot system. Among the existing object tracking technologies, cam shift technology is a technique of tracking an object using color information of an object. Recently, digital image data using infrared camera functions are widely used due to various demands of digital image equipment. However, the existing cam shift method can not track objects in image data without color information. Our proposed tracking algorithm tracks the object by analyzing the color if valid color information exists in the digital image data, otherwise it generates the lightness feature information and tracks the object through it. The brightness feature information is generated from the ratio information of the width and the height of the area divided by the brightness. Experimental results shows that our tracking algorithm can track objects in real time not only in general image data including color information but also in image data captured by an infrared camera.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제11권2호
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• pp.118-123
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• 2011

Video based object tracking normally deals with non-stationary image streams that change over time. Robust and real time moving object tracking is considered to be a problematic issue in computer vision. Multiple object tracking has many practical applications in scene analysis for automated surveillance. In this paper, we introduce a specified object tracking based particle filter used in an environment of multiple moving objects. A differential image region based tracking method for the detection of multiple moving objects is used. In order to ensure accurate object detection in an unconstrained environment, a background image update method is used. In addition, there exist problems in tracking a particular object through a video sequence, which cannot rely only on image processing techniques. For this, a probabilistic framework is used. Our proposed particle filter has been proved to be robust in dealing with nonlinear and non-Gaussian problems. The particle filter provides a robust object tracking framework under ambiguity conditions and greatly improves the estimation accuracy for complicated tracking problems.

• 융합신호처리학회논문지
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• 제4권4호
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• pp.1-6
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• 2003

본 논문에서는, 움직이는 영상을 충돌방지 시스템에 의해 검출한다. 이런 영상의 노이즈는 평균 필터로 제거시킨다. 그리고, 이진 차 영상을 이용하여 움직임이 감지되었을 경우에는 라벨링과 투영방법에 의해 움직임 영역만 정확히 추출하였다. 그 후에 시스템의 추적모드에 의해서 이미지가 천천히 움직일 경우 추적창의 중심은 이전 프레임의 추적창으로부터 이동한다. 그리고, 추적 창은 추적모드와 탐지모드로 나누고, 차 영상 데이터의 대차 상관 값에 의해 결정하였다. 탐지모드는 외란에 의한 에러를 감소하기 위해서 탐지-시간 값의 비교로 추적단계를 계속 진행할 것인지 아닌지를 결정하였다. 이와 같은 움직이는 영상의 탐지와 추적을 시뮬레이션으로 확인하였다.

• Journal of Electrical Engineering and information Science
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• 제3권2호
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• pp.230-238
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• 1998

When size and shape of moving object have been changed, a correlator often accumulates walk-off error. A success of correlation-based tracking largely depends on choosing suitable window size and position and thus transferring the proper reference image to the next frame. For this, we propose the Adaptive Window Algorithm with Four-Direction Sizing Factors (AWA-FSF) for fast adjusting a reference region to enhance reliability of correlation-based image tracking in complex cluttered environments. Since the AWA-FSF is capable of adjusting a reference image size more rapidly and properly, we can minimize the influence of complex background and clutter. In addition, we can finely tune the center point of the reference image repeatedly after main tracking process. Thus we have increased stability and reliability of correlation-based image tracking. We tested performance of the AWA-FSF using 45 real image sequences made of over 3400 images and had the satisfied results for most of them.

• 제어로봇시스템학회논문지
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• 제17권4호
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• pp.388-396
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• 2011

Sun tracking system is the most important subsystem in parabolic dish type solar thermal power plant, since it determines the amount of thermal energy to be collected, thus affects the efficiency of solar thermal power plant most significantly. Various types of sun tracking systems are currently used. Among them, use of photo sensors to located the sun(which is called sensor type) and use of astronomical algorithm to compute the sun position(which is called program type) are two of the mostly used methods. Recently some uses CCD sensor, like CCD camera, which is called image processing type sun tracking system. This work is concerned with the analysis of sun tracking performance of various types of sun tracking systems currently used in the parabolic dish type solar thermal power plant. We first developed a sun tracking error measurement system. Then, we evaluate the performance of five different types of sun tracking systems, sensor type, program type, hybrid type(use of sensor and computed sun position simultaneously), tracking error compensated program type and image processing type. Experimentally obtained data shows that the tracking error compensated program type sun tracking system is very effective and could provide a good sun tracking performance. Also the data obtained shows that the performance of sensor type sun tracking system is being affected by the cloud significantly, while the performance of a program type sun tracking system is being affected by the sun tracking system's mechanical and installation errors very much. Finally image processing type sun tracking system can provide accurate sun tracking performance, but costs more and requires more computational time.

• 한국컴퓨터정보학회논문지
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• 제22권12호
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• pp.55-61
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• 2017

In this paper, we propose a novel tracking method using target separation and detection that are based on discriminative correlation filter (DCF), which is studied a lot recently. 'Retainability' is one of the most important factor of tracking. There are some factors making retainability of tracking worse. Especially, fast movement and occlusion of a target frequently occur in image data, and when it happens, it would make target lost. As a result, the tracking cannot be retained. For maintaining a robust tracking, in this paper, separation of a target is used so that normal tracking is maintained even though some part of a target is occluded. The detection algorithm is executed and find new location of the target when the target gets out of tracking range due to occlusion of whole part of a target or fast movement speed of a target. A variety of experiments with various image data sets are conducted. The algorithm proposed in this paper showed better performance than other conventional algorithms when fast movement and occlusion of a target occur.

• 한국지능시스템학회논문지
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• 제22권2호
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• pp.198-204
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• 2012

로봇들의 협동 작업을 위해서는 다양한 환경에서 다른 로봇들을 인식하고 추적하는 기술이 요구된다. 본 논문에서는 코드북 모델과 스테레오 영상 처리를 이용하여 이동 로봇을 인식하고, 퍼지 제어기를 사용해 추적하는 이동 로봇 추적 제어 시스템을 제안한다. 먼저 코드북 모델을 사용하여 영상의 전경과 배경을 분리하였다. 분리된 전경에서 색상정보를 기반으로 관심영역을 구해내고, 스테레오 영상처리를 통해 얻은 깊이 영상을 기반으로 이동 로봇까지의 실제 거리를 추정한다. 각 거리에 따라 열림 및 닫힘 연산을 적용하고, 모듈형 로봇의 크기에 맞춰 라벨링을 통해 효과적으로 이동 로봇을 인식한다. 추출된 이동 로봇의 움직임에 따른 효과적인 추적을 위하여 스테레오 영상 처리를 통해 얻은 거리 정보와 로봇의 이동 정보를 이용해 퍼지 제어기를 설계하여 이동 로봇 추적 시스템을 제안하였다. 제안한 퍼지 추적 제어 시스템의 성능은 실제 이동 로봇의 추적 실험을 통하여 검증하였다.

• 제어로봇시스템학회논문지
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• 제11권7호
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• pp.587-594
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• 2005

In this paper, a robust correlation-based video tracking is proposed to track a moving object in correlated image sequences. A correlation-based video tracking algorithm seeks to align the incoming target image with the reference target block image, but has critical problems, so called a false-peak problem and a drift phenomenon (correlator walk-off. The false-peak problem is generally caused by highly correlated background pixels with similar intensity of a moving target and the drift phenomenon occurs when tracking errors accumulate from frame to frame because of the nature of the correlation process. At first, the false-peaks problem for the ordinary correlation-based video tracking is investigated using a simple mathematical analysis. And, we will suggest a robust selective-attention correlation measure with a gradient preprocessor combined by a drift removal compensator to overcome the walk-off problem. The drift compensator adaptively controls the template block size according to the target size of interest. The robustness of the proposed method for practical application is demonstrated by simulating two real-image sequences.