• 한국콘텐츠학회논문지
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• 제15권2호
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• pp.11-20
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• 2015

본 논문에서는 무인 자동 추적 감시를 위한 이진 CDMA 기반 지능형 이동 감시 시스템을 개발한다. 이는 기본적으로 CDMA와 TDMA의 장점을 복합적으로 적용한 이진 CDMA 무선 통신 기술을 이용하여 지능형 감시 시스템을 구현한다. 본 시스템은 네트워크상에서 실시간으로 현지 상황을 모니터링 할 수 있으며, 동시에 보안 감시 체계를 구현하여 다양한 상황별로 처리하도록 하였다. 개발된 시스템은 카메라를 이용한 객체의 360도 추적, PTZ(Pan/Tilt/Zoom) 카메라의 줌 기능에 의한 영상 확대, 영상 내 이동 객체의 식별 및 식별된 영상의 원거리 전송이 가능하다. 마지막으로, 대상 객체에 대한 감시 범위, 객체 확대 기능, 객체 탐지 수, 원격 전송된 영상 모니터링, 영상 출력 신호에 따른 초당 프레임 수 등과 같은 상황 설정한 모의실험을 통해 본 구현 시스템을 보여 줄 것이다.

• Journal of information and communication convergence engineering
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• 제8권2호
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• pp.145-149
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• 2010

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

• 한국정보통신학회논문지
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• 제6권7호
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• pp.1126-1132
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• 2002

In this paper, we propose a new scheme of motion tracking based on fuzzy inference (Fl) and wavelet transform (WT) from image sequences. First, we present a WT to segment a feature extraction of dynamic image . The coefficient matrix for 2-level DWT tent to be clustered around the location of Important features in the images, such as edge discontinuities, peaks, and corners. But these features are time varying owing to the environment conditions. Second, to reduce the spatio-temperal error, We develop a fuzzy inference algorithm. Some experiments are performed 0 testify the validity and applicability of the proposed system As a result, proposed method is relatively simple compared with the traditional space domain method. It is also well suited for motion tracking under the conditions of variation of illumination.

• 항공우주기술
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• 제11권2호
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• pp.140-148
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• 2012

자율 주행을 위해 주행 지도, 위치 추적 및 목적지까지의 최단 경로 설정 연구가 필요하다. 특히 실내에서는 GPS 신호를 수신 받을 수 없기 때문에 이미지 프로세싱과 같은 방법을 통해 현재 위치를 인식하고 3차원 지도를 생성해야 한다. 본 논문에서는 Depth 카메라인 키넥트를 이용하여 3차원 지도를 생성하고, 일반 카메라로 촬영한 2차원 이미지를 이용하여 3차원 지도에서 현재 위치를 파악하는 방법에 대해 설명한다. 그리고 지도에서 장애물을 확인하고 단순화하는 방법에 대해서도 설명한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.525-528
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• 2002

This study describes an implementation of object tracking algorithm on FPGA. The global system detect the zone there is more motion in, attending to the generated optical flow, and centers its attention to it to improve the details In this case, To obtain image in Camera, Image aquisition board make use of SAA7113 Video Input processor and algorithm is applied to motion estimation and difference picture. Also, This work can be applied kalman filter to reliability of tracking.

• Journal of Mechanical Science and Technology
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• 제18권7호
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• pp.1236-1245
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• 2004

In this study, an optical imaging method was developed for the measurements of the sizes and velocities of droplets in sprays. Double-exposure single-frame spray images were captured by the imaging system. An image processing program was developed for the measurements of the sizes and positions of individual particles including separation of the overlapped particles and particle tracking and pairing at two time instants. To recognize and separate overlapping particles, the morphological method based on watershed segmentation as well as separation using the perimeter and convex hull of image was used consecutively. Better results in separation were obtained by utilization of both methods especially for the multiple or heavily-overlapped particles. The match probability method was adopted for particle tracking and pairing after identifying the positions of individual particles and it produced good matching results even for large particles like droplets in sprays. Therefore, the developed optical imaging method could provide a reliable way of analyzing the motion and size distribution of droplets produced by various sprays and atomization devices.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권8호
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• pp.3011-3024
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• 2021

Pose estimation of the sensor is important issue in many applications such as robotics, navigation, tracking, and Augmented Reality. This paper proposes visual-inertial integration system appropriate for dynamically moving condition of the sensor. The orientation estimated from Inertial Measurement Unit (IMU) sensor is used to calculate the essential matrix based on the intrinsic parameters of the camera. Using the epipolar geometry, the outliers of the feature point matching are eliminated in the image sequences. The pose of the sensor can be obtained from the feature point matching. The use of IMU sensor can help initially eliminate erroneous point matches in the image of dynamic scene. After the outliers are removed from the feature points, these selected feature points matching relations are used to calculate the precise fundamental matrix. Finally, with the feature point matching relation, the pose of the sensor is estimated. The proposed procedure was implemented and tested, comparing with the existing methods. Experimental results have shown the effectiveness of the technique proposed in this paper.

• Journal of Platform Technology
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• 제6권4호
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• pp.18-25
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• 2018

This paper describes a real-time human and robot tracking method in Intelligent Space with multi-camera networks. The proposed method detects candidates for humans and robots by using the histogram of oriented gradients (HOG) feature in an image. To classify humans and robots from the candidates in real time, we apply cascaded structure to constructing a strong classifier which consists of many weak classifiers as follows: a linear support vector machine (SVM) and a radial-basis function (RBF) SVM. By using the multiple view geometry, the method estimates the 3D position of humans and robots from their 2D coordinates on image coordinate system, and tracks their positions by using stochastic approach. To test the performance of the method, humans and robots are asked to move according to given rectangular and circular paths. Experimental results show that the proposed method is able to reduce the localization error and be good for a practical application of human-centered services in the Intelligent Space.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2009년도 학술대회
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• pp.411-417
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• 2009

본 논문은 지능형 환경에 적합하도록 사용자의 자유를 제한하지 않는 실시간 신체 부위 추적 시스템의 구현에 관해 다룬다. 본 시스템은 기존의 신체 부위 추적 시스템과 달리 소매의 길이에 제약 없이 긴 소매, 반 소매 모두 인식할 수 있도록 함으로써 시스템의 generality를 높였다. 정확한 인식을 위하여, 한 대의 카메라에서 얻어진 이미지에서 손, 머리, 발의 신체 부위를 따로 검출하고 각 신체 부위를 검출할 때 해당 부위에 적합한 특징점을 따로 선택하여 검출하였다. 검출된 2차원의 신체 부위들을 calibrate된 카메라를 이용하여 3차원 자세로 변환하였다. 본 시스템은 실험을 통해 실시간(50fps) 성능으로 향상된 손 추적 성능을 보여주었다.

• 한국운동역학회지
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• 제17권1호
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• pp.81-90
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• 2007

The effort identifying positioning information of the moving object in real time has been a issue not only in sport biomechanics but also other academic areas. In order to solve this issue, this study tried to track the movement of a pitched ball that might provide an easier prediction because of a clear focus and simple movement of the object. Machine learning has been leading the research of extracting information from continuous images such as object tracking. Though the rule-based methods in artificial intelligence prevailed for decades, it has evolved into the methods of statistical approach that finds the maximum a posterior location in the image. The development of machine learning, accompanied by the development of recording technology and computational power of computer, made it possible to extract the trajectory of pitched baseball from recorded images. We present a method of baseball tracking, based on object tracking methods in machine learning. We introduce three state-of-the-art researches regarding the object tracking and show how we can combine these researches to yield a novel engine that finds trajectory from continuous pitching images. The first research is about mean shift method which finds the mode of a supposed continuous distribution from a set of data. The second research is about the research that explains how we can find the mode and object region effectively when we are given the previous image's location of object and the region. The third is about the research of representing data into features that we can deal with. From those features, we can establish a distribution to generate a set of data for mean shift. In this paper, we combine three works to track baseball's location in the continuous image frames. From the information of locations from two sets of images, we can reconstruct the real 3-D trajectory of pitched ball. We show how this works in real pitching images.