• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(4)
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• pp.89-92
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• 2001

In this paper, we propose a new approach for tracking a moving object in moving image sequences using active contour models and optical flow. In our approach object segmentation is achieved by active contours, and object tracking is done by motion estimation based on optical flow. To get more dynamic characteristics, Lagrangian dynamics combined to the active contour models. For the optical flow computation, a method, which is based on Spatiotempo-ral Energy Models, is employed to perform robust tracking under poor environments. A prototype real tracking system has been developed and applied to a contents-based video retrieval systems.

• 로봇학회논문지
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• 제7권2호
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• pp.113-119
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• 2012

In this paper we propose the method that detects moving objects in autonomous navigation vehicle using LRF sensor data. Object detection and tracking methods are widely used in research area like safe-driving, safe-navigation of the autonomous vehicle. The proposed method consists of three steps: data segmentation, mobility classification and object tracking. In order to make the raw LRF sensor data to be useful, Occupancy grid is generated and the raw data is segmented according to its appearance. For classifying whether the object is moving or static, trajectory patterns are analysed. As the last step, Markov chain Monte Carlo (MCMC) method is used for tracking the object. Experimental results indicate that the proposed method can accurately detect moving objects.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 춘계학술대회 논문집
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• pp.254-258
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• 1996

In this paper, we proposed realtime visual tracking system of moving object for 2D target using extended Kalman Filter Algorithm. A targeting marker are recongnized in each image frame and positions of targer object in each frame from a CCD camera while te targeting marker is attached to the tip of the SCARA robot hand. After the detection of a target coming into any position of the field-of-view, the target is tracked and always made to be located at the center of target window. Then, we can track the moving object which moved in inter-frames. The experimental results show the effectiveness of the Kalman filter 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

• 한국항행학회논문지
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• 제5권1호
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• pp.26-36
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• 2001

시 변환 영상에서 가장 중요한 문제 중의 하나는 자동 목표 추적이다. 본 논문에서는 퍼지 예측을 이용한 이동물체의 위치예측 및 추적 기법을 제안한다. 먼저, 누적 차영상을 이용하여 물체와 배경을 분리한 다음 이동물체를 추출한다. 그리고 추출된 물체에 무게 중심법을 이용하여 물체의 중심점을 추출하고 추출된 물체에 가변 크기 탐색창을 사용하여 추적 성능을 높일 수 있는 기법을 제안한다. 또한 효율적인 물체 추적을 위한 조건으로 비선형적인 예측이 필요한데 본 논문에서는 다음 프레임에서의 물체의 위치를 예측하기 위해 퍼지 예측 방법을 제안한다. 실험을 통해 제안된 퍼지 예측 시스템이 여러 상황하에서 이동물체를 안정적으로 추적함을 보인다.

• International Journal of Control, Automation, and Systems
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• 제3권3호
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• pp.444-452
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• 2005

A new scheme for a mobile robot to track and capture a moving object using camera images is proposed. The moving object is assumed to be a point-object and is projected onto an image plane to form a geometrical constraint equation that provides the position data of the object based on the kinematics of the active camera. Uncertainties in position estimation caused by the point-object assumption are compensated for using the Kalman filter. To generate the shortest time path to capture the moving object, the linear and angular velocities are estimated and utilized. In this paper, the experimental results of the tracking and capturing of a target object with the mobile robot are presented.

• 한국항행학회논문지
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• 제18권4호
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• pp.387-392
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• 2014

최근 지능형 비디오 감시를 위한 다양한 연구가 제안되고 있음에도 CCTV 영상에서 이상 징후 판단이 사람에 의해 이루어지고 있어 상황인식을 위한 방법 및 연구가 필요하다. 본 논문에서는 이동물체 검출 및 추적을 위해 RGB 칼라 모델 기반의 색도 영상과 엔트로피 영상을 도출하여 그림자 제거를 수행한 후 이동물체를 추적하는 방법을 제안한다. 이동물체 검출을 위해 잡음 및 주위환경변화에 민감하지만 순간적으로 발생되는 상황인지 환경에서 효과적인 차영상 모델을 적용하였다. 검출한 이동물체 영역에서 RGB 채널의 색도 영상을 기반으로 첫 번째 그림자 후보 영역을 선정하였고, 그레이레벨에서 엔트로피를 계산하여 두 번째 그림자 후보 영역을 추정하여 그림자를 제거하였다. 제안하는 방법의 타당성을 위해 고속도로에서 주행하는 자동차들을 대상으로 실험하였고, 실험 결과 색상과 엔트로피를 이용한 그림자를 제거와 이동물체 추적이 효과적으로 수행됨을 확인하였다.

• 제어로봇시스템학회논문지
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• 제4권2호
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• pp.187-193
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• 1998

This paper proposes an advanced visual tracking algorithm for the stable grasping of a moving target(2D). This algorithm is programmed to find grasping points of an unknown polygonal object and execute visual tracking. The Kalman Filter(KF) algorithm based on the SVD(Singular Value Decomposition) is applied to the visual tracking system for the tracking of a moving object. The KF based on the SVD improves the accuracy of the tracking and the robustness in the estimation of state variables and noise statistics. In addition, it does not have the numerical unstability problem that can occur in the visual tracking system based on Kalman filter. In the grasping system, a parameterized family is constructcd, and through the family, the grasping system finds the stable grasping points of an unknown object through the geometric properties of the parameterized family. In the previous studies, many researchers have been studied on only 'How to track a moving target'. This paper concern not only on 'how to track' but also 'how to grasp' and apply the grasping theory to a visual tracking system.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.1055-1058
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• 2003

The robustness and reliability of vision algorithms is the key issue in robotic research and industrial applications. In this paper robust real time visual tracking in complex scene is considered. A common approach to increase robustness of a tracking system is the use of different model (CAD model etc.) known a priori. Also fusion or multiple features facilitates robust detection and tracking of objects in scenes of realistic complexity. Voting-based fusion of cues is adapted. In voting. a very simple or no model is used for fusion. The approach for this algorithm is tested in a 3D Cartesian robot which tracks a toy vehicle moving along 3D rail, and the Kalman filter is used to estimate the motion parameters. namely the system state vector of moving object with unknown dynamics. Experimental results show that fusion of cues and motion estimation in a tracking system has a robust performance.

• 제어로봇시스템학회논문지
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• 제14권10호
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• pp.998-1004
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• 2008

In this paper, a visual servoing control technique of humanoid robot arms is implemented for tracking a moving object. An embedded time-delayed controller is designed on an FPGA(Programmable field gate array) chip and implemented to control humanoid robot arms. The position of the moving object is detected by a stereo vision camera and converted to joint commands through the inverse kinematics. Then the robot arm performs visual servoing control to track a moving object in real time fashion. Experimental studies are conducted and results demonstrate the feasibility of the visual feedback control method for a moving object tracking task by the humanoid robot arms called the ROBOKER.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.41.3-41
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• 2002

Motion estimation using Full-Search(FS) and Block-Matching Algorithm(BMA) is often used in the case of moving object tracking by vision sensors. However these methods often miss the real-time vision data because these schemes suffer the heavy computational load. When the image size of moving object is changed in an image frame according to the distance between the camera of mobile robot and the moving object, the tracking performance of a moving object may decline with these methods because of the shortage of active handling. In this paper, the variable-representative block that can reduce a lot of data computations, is defined and optimized by changing the size of representative block accor...