• 한국통신학회논문지
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• 제23권9A호
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• pp.2258-2270
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• 1998

Recently, the distributed processing environments provide various open multimedia serivces through telecommunication network and have been developing into information networking structure based on object oriented concepts and distributed systems which can apply new services with a few changes the existing networks. This paper proposes the object group model which is the collection of objects and can functionally and efficiently manage the individual object. this paper presents the analysis of the requirement and the function specifications to propose the object group model, and depicts the functional structure in details using its analysis. The goal of this paper is to decrease the complexity of the object's management and to voercome the limitations of among the components of object group for management and service functions based on our proposed the object group model and show interaction procedures to eTD (event tracing diagram)s and finally we design the object group model by TINA-ODL.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.410-412
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• 2021

본 논문은 객체와 배경 히스토그램을 활용한 개선된 보행자 검출 방식을 제안하고 있다. HOG & SVM 알고리즘을 통해 검출한 객체는 사각형 형태로 검출된다. 사각형 영역 안에는 배경과 객체의 영역이 혼합되어있다. 배경을 제외한 객체의 영역만을 검출한다면 객체 관련 다양한 정보를 쉽게 얻을 수 있다. 검출된 사각형의 크기를 객체의 크기에 맞게 x-y축 투영 알고리즘을 사용하여 재조정한다. 그리고 나서 재조정 된 사각형 내의 객체에 대한 히스토그램을 바탕으로 배경과 객체를 구분하여 개선된 객체를 검출한다. 검출한 객체와 원본의 객체를 비교하는 신뢰성 평가인 정밀도와 재현율의 평균값이 각각 97.9%와 90%를 보이고 있다.

• 전기학회논문지
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• 제64권7호
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• pp.1047-1055
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• 2015

We proposes a method for improving the identification and tracking of the moving objects in intelligent video surveillance system. The proposed method consists of 3 parts: object detection, object recognition, and object tracking. First of all, we use a GMM(Gaussian Mixture Model) to eliminate the background, and extract the moving object. Next, we propose a labeling technique forrecognition of the moving object. and the method for identifying the recognized object by using the optical flow and EMD algorithm. Lastly, we proposes method to track the location of the identified moving object regions by using location information of moving objects and Kalman filter. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.

• 전기학회논문지
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• 제65권12호
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• pp.2057-2060
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• 2016

Range-based motion estimation of a moving object by using a camera is proposed. Whereas the existing results constrain the motion of an object for the motion estimation of an object, the constraints on the motion is relieved in the proposed method in that a more generally moving object motion can be handled. To this end, a nonlinear observer is designed based on the relative dynamics between the object and camera so that the object velocity and the unknown camera velocity can be estimated. Stability analysis and simulation results for the moving object are provided to show the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.62-67
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• 2005

Object recognition in the field of robotics generally has depended on a computer vision system. Recently, RFID(Radio Frequency IDentification) technology has been suggested to support recognition and has been rapidly and widely applied. This paper introduces the more advanced RFID-based recognition. A novel tag named 3D tag, which facilitates the understanding of the object, was designed. The previous RFID-based system only detects the existence of the object, and therefore, the system should find the object and had to carry out a complex process such as pattern match to identify the object. 3D tag, however, not only detects the existence of the object as well as other tags, but also estimates the orientation and position of the object. These characteristics of 3D tag allows the robot to considerably reduce its dependence on other sensors required for object recognition the object. In this paper, we analyze the 3D tag's detection characteristic and the position and orientation estimation algorithm of the 3D tag-based RFID system.

• 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.

• 한국정밀공학회지
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• 제16권7호
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• pp.125-131
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• 1999

In this paper, the algorithms which can track the two dimensional moving circular object using simple vision system are described. In order to track the moving object, the process of finding the object feature points - such as centroid of the object, corner points, area - is indispensable. With the assumption of two-dimensional circular moving object, the centroid of the circular object is computed from three points on the object circumference. Different kinds of algorithms for computing three edge points - simple x directional detection method, stick method. T-shape method are suggested. Through the computer simulation and experiments, three algorithms are compared from the viewpoint of detection accuracy and computational time efficiency.

• 정보기술과데이타베이스저널
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• 제7권1호
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• pp.17-26
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• 2000

To provide highly available services in the distributed object system, it is required to support the object group. The state machine approach and primary-backup approach are proposed as two representative approaches for support of object group. The primary-backup approach does not only give merits such as transparency of object group and non-deterministic execution but also require less resource than state machine approach. This paper describes an extension of CORBA that is required to support of the primary-backup object group. In this paper, the state of backup is synchronized with primary through the atomic multicast protocol whenever the request of client is executed at primary. As a result, it does not require message logging and check pointing. The object group of this paper also provides fast response time in case of failure of the primary since it makes primary election unnecessary. And through an extension of IDL, it makes possible to avoid consistency control depending on characteristic of application. A prototype has been implemented and the performance of object group has been compared with a single object invocation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.262-265
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• 1999

This paper describes a new method for object extraction necessary for image tracking systems. The extraction method which this paper proposes here is that an M-array is set between a camera and the object and the obtained image including the object and M-array is pro-cessed for extracting the object. The image processing utilizes a characteristic of M-array which is robust to noise. When an M-array is overlapped on the object in background image, the object woud have a part of M-array, which is detected by use of partial correlation between the mosaic image of M-array and the standard M-array. Thus the shape and position of the object are extracted by extracting a common domain of width of high correlation value. Experiments are carried out by using an actual photo of Kumamoto city taken from an airplane as background, and by use of a rectangular and circular object. The results of experiment show a wide application of this method for practical image tracking systems.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2358-2361
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• 2001

In recent years there have been increasing interests in real-time object tracking with image information. Since image information is affected by illumination, this paper presents the real-time object tracking method based on neural networks which have robust characteristics under various illuminations. This paper proposes three steps to track the object and the fast tracking method. In the first step the object color is extracted using neural networks. In the second step we detect the object feature information based on invariant moment. Finally the object is tracked through a shape recognition using neural networks. To achieve the fast tracking performance, this paper first has a global search of entire image and tracks the object through local search when the object is recognized.