• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.47-48
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• 2013

본 논문에서는 이동 카메라 환경에서 이동물체 추적을 위한 영상 분할에 대하여 연구하였다. 입력영상으로 부터 이동물체영역을 분할하기위하여 입력영상에 대하여 윤곽선을 구한 다음 윤곽선 영역에 대하여 BMA을 이용하여 이동벡터를 구한다. 구해진 이동벡터를 같은 특성의 벡터들을 분류하여 이동물체를 분할한다. 제안된 알고리즘이 다중 이동물체의 분할이 가능하였다.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.231-242
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• 2007

The existing pattern mining methods[1,2,3,4,5,6,11,12,13] do not use location generalization method on the set of location history data of moving object, but even so they simply do extract only frequent patterns which have no spatio-temporal constraint in moving patterns on specific space. Therefore, it is difficult for those methods to apply to frequent pattern mining which has spatio-temporal constraint such as optimal moving or scheduling paths among the specific points. And also, those methods are required more large memory space due to using pattern tree on memory for reducing repeated scan database. Therefore, more effective pattern mining technique is required for solving these problems. In this paper, in order to develop more effective pattern mining technique, we propose new location generalization method that converts data of detailed level into meaningful spatial information for reducing the processing time for pattern mining of a massive history data set of moving object and space saving. The proposed method can lead the efficient spatial moving pattern mining of moving object using by creating moving sequences through generalizing the location attributes of moving object into 2D spatial area based on $R^*$-Tree and Area Grid Hash Table(AGHT) in preprocessing stage of pattern mining.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.157-162
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• 2002

Recently, location based services, which make use of location information of moving objects, have obtained increasingly high attention. The moving objects are time-evolving spatial objects, that is, their locations are dynamically changed as time varies. Generally, GIS server stores and manages the spatial objects, of which locations are rarely changed. The traditional GIS server, however, has a difficulty to manage the moving objects, due to the fact of locations being frequently changed and the trajectory information (past locations of moving objects) being managed. In this paper, we have designed a moving object server, which stores and manages the locations in order to support various location based services. The moving object server is composed of a location acquisition component, a location storage component, and a location query component. The contribution of this paper is that we integrate the each work for location acquisition, storage, and query into a moving objects server.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.3
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• pp.158-166
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• 2011

Generally, moving object tracking used Lucas-Kanade feature tracking method which is strong in movement, rotation and size. But this method is very weak of occlusion by background or another object and so on. In this case, this method tracks backgrounds or another objects instead a moving object, or a tracking is finished. In order to solve this problem, we proposes Lucas-Kanade feature tracking method which introduce a destimation function and prediction function.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.257-259
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• 1996

This paper presents the active eye system for tracking a moving object in 3D space. A prototype system able to track a moving object is designed and implemented. The mechanical system ables the control of platform that consists of binocular camera and also the control of the vergence angle of each camera by step motor. Each camera has two degrees of freedom. The image features of the object are extracted from complicated environment by using zero disparity filtering(ZDF). From the cnetroid of the image features the gaze point on object is calculated and the vergence angle of each camera is controlled by step motor. The Proposed method is implemented on the prototype with robust and fast calculation time.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.6
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• pp.175-182
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• 1998

An advanced visual tracking and stable grasping algorithm for a moving object is proposed. The stable grasping points for a moving 2D polygonal object are obtained through the visual tracking system with the Kalman filter and image prediction technique. The accuracy and efficiency are improved more than any other prediction algorithms for the tracking of an object. In the processing of a visual tracking. the shape predictors construct the parameterized family and grasp planner find the grasping points of unknown object through the geometric properties of the parameterized family. This algorithm conducts a process of ‘stable grasping and real time tracking’.

• Korean Journal of Optics and Photonics
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• v.6 no.4
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• pp.274-281
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• 1995

The new method of recording and reconstructing a synthetic object, which was called as scannedobject holography (SOH), was proposed and its feasibility was demonstrated theoretically and experimentally. The hologram was recorded by interfering the fixed reference beam with spherical waves emitting from a moving point source, whose trajectory determined the shape of the synthetic object to be recorded. The end face of an optical fiber and the output from a pulsed laser were utilized in order to implement a moving point source experimentally. tally.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.4
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• pp.415-425
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• 2019

This study proposes a new approach to control Moving Stuff Action Through Iterative Learning robot with dual arm for smart factory. When robot moves object with dual arm, not only position of each hand but also contact force at surface of an object should be considered. However, it is not easy to determine every parameters for planning trajectory of the an object and grasping object concerning about variety compliant environment. On the other hand, human knows how to move an object gracefully by using eyes and feel of hands which means that robot could learn position and force from human demonstration so that robot can use learned task at variety case. This paper suggest a way how to learn dynamic equation which concern about both of position and path.

• Journal of the Korea Society of Computer and Information
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• v.16 no.9
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• pp.131-143
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• 2011

Previous alerting service based on LBS was caused severe overload problem of server by using the method to confirm the location of each moving object on server. In this paper, by loading an App on smart moving object, we proposed a novel algorithm named ADAS(Active Disaster Alert Service) for accessing to the server site with oneself location information as needed and implemented the disaster alerting service system with visualization for user. In the proposed method, running App access to the server periodically with the present location coordinate gained from GPS module or network module and the ID of moving object. Then, the server compare the present location coordinate of moving object and the coordinates of disasters registered in DIDB and transmit the n NDIs existed in near distance orderly from the coordinate of present moving object to the client. The App compares the coordinate of present location for moving object and the coordinates of NDI is transmitted from server by real time and executes the service with classifying levels of alert into three steps such as danger, carefulness and safety. And new NDIs are gained by accessing DIDB on Server periodically during running App. Therefore, this will be become a novel method for reducing fundamentally the server overload problem in comparison with previous alerting service that the career of moving object is managed on server.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.15-22
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• 2005

This paper proposed a object tracking algorithm which can track contour of fast moving object through motion estimation. Since the proposed tracking algorithm is based on the radial representation, the motion estimation of object can be accomplished at the center of object with the low computation complexity. The motion estimation of object makes it possible to track object which move fast more than distance from center point to contour point for each frame. In addition, by introducing both gradient image and difference image into energy functions in the process of energy convergence, object tracking is more robust to the complex background. The results of experiment show that the proposed algorithm can track fast moving object in real-time and is robust under the complex background.