• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.622-632
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• 1999

As the complexity of software development is increasing due to networking, multimedia, and diverse system architecture, the need for effective software development methodology is increasing. Especially, due to software standard and internalization of software market, it is necessary to accept international quality such as ISO 9000-3. In addition, object oriented development methodology is required due to rapid propagation of OO technology and standardization. Recently, UML was accepted by the OMG as standard object-oriented modeling language for distributed environment. When we UML was accepted by the OMG as standard object-oriented modeling language for distributed environment. When we develop Java and CORBA-based software, often UML is applied to Java and CORBA-based projects. However, current structural or OMT-based object-oriented methodologies. In this paper, we proposed UML-based development and concrete guidelines for each phase in order to apply UML to software development practically and effectively. Also, we define the transition guidelines and semantics between various development tasks. In addition, the analysis and design techniques of user interface and system development techniques needed in Web application development are presented.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.1
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• pp.39-45
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• 2019

We propose an active color model based method for tracking motions of multiple human using a networked multiple-camera system in IoT space as a human-robot coexistent system. An IoT space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of IoT space as well. One of the main goals of IoT space is to assist humans and to do different services for them. In order to be capable of doing that, IoT space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly. In the environment where many camera modules are distributed on network, it is important to identify object in order to track it, because different cameras may be needed as object moves throughout the space and IoT space should determine the appropriate one. This paper describes appearance based unknown object tracking with the distributed vision system in IoT space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

• Journal of Digital Convergence
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• v.12 no.8
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• pp.337-343
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• 2014

This paper proposes a minimal contour tracking algorithm that reduces transmission of data for tracking mobile objects in surveillance networks in terms of detection and communication load. This algorithm perform detection for object tracking and when it transmit image data to server from camera, it minimized communication load by reducing quantity of transmission data. This algorithm use minimal tracking area based on the kinematics of the object. The modeling of object's kinematics allows for pruning out part of the tracking area that cannot be mechanically visited by the mobile object within scheduled time. In applications to detect an object in real time,when transmitting a large amount of image data it is possible to reduce the transmission load.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.224-229
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• 2008

In this paper, we propose an object control system on table top display to support augmented reality in which objects in real-world control computer-generated data. We developed LED-based object control system over table top display so that it is capable of controlling networked table top display. The LED-based object control system supports more natural interactive interface. In this paper, infrared LED is used to implement the object control device to be recognised by table top display. We applied LED-based object control system in air hockey game where a team has a point if their puck goes to opponent's net on a table. Since users can control objects in cyber world with the proposed object control device, it is realized augmented reality.

• Journal of Convergence for Information Technology
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• v.12 no.1
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• pp.39-44
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• 2022

The purpose of this study is to extract the type, location, and absolute size of an object in an image using a deep learning algorithm, predict the relative distance between objects, and use this to detect contact between objects. To analyze the size ratio of objects, YOLO, a CNN-based object detection algorithm, is used. Through the YOLO algorithm, the absolute size and position of an object are extracted in the form of coordinates. The extraction result extracts the ratio between the size in the image and the actual size from the standard object-size list having the same object name and size stored in advance, and predicts the relative distance between the camera and the object in the image. Based on the predicted value, it detects whether the objects are in contact.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.97-100
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• 2000

This paper presents a new approach to the vertex based shape coding technique. The conventional approaches encode objects using a spline method with the same distortion coefficients. The proposed approach, however, classifies the objects based on the object's features, and then applies different distortion values depending on the classified object types. Using this pre-classifying technique, this paper reduces the bit rate and the computational complexity necessary for the encoding process. The performance of the proposed method has been proved by experiments on the various sample Images.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.546-546
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• 2000

This paper designs and implements special objects such as a control object, a I/O object and a file object based on CORBA and DCOM which are suitable to distributed control systems. And interactions among those objects ate analyzed.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.73-76
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• 2002

This paper has been studied an algorithm for segmenting gaseous object images. A new methodology for segmenting gaseous object images is introduced. Proposed method consists offuzzy-based boundary detector applicable to gaseous as well as rigid objects and concave region filling to recover object regions.

• Journal of KIISE:Databases
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• v.27 no.1
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• pp.1-12
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• 2000

Many object oriented database systems manage object buffers to provide fast access to objects. Traditional buffer replacement algorithms based on fixed length pages simply assume that the cost incurred by operating a buffer is propertional to the number of buffer faults. However, this assumption no longer holds in an objects buffer where objects are of variable length and the cost of replacing an object varies for each object. In this paper, we propose a cost based replacement algorithm for object buffers. The proposed algorithm replaces the have minimum costs per unit time and unit space. The cost model extends the previous page based one to include the replacement costs and the sizes of objects. The performance tests show that proposed algorithm is almost always superior to the LRU-2 algorithm and in some cases is more than twice as fast. The idea of cost based replacement can be applied to any buffer management architectures that adopt earlier algorithms. It is especially useful in object oriented database systems where there is significant variation in replacement costs.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.15-29
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• 2018

This paper proposes an enhanced object tracking algorithm to compensate the lack of temporal information in existing particle swarm optimization based object trackers using the trajectory of the target object. The proposed scheme also enables the tracking and documentation of the location of an online updated set of distractions. Based on the trajectories information and the distraction set, a rule based approach with adaptive parameters is utilized for occlusion detection and determination of the target position. Compare to existing algorithms, the proposed approach provides more comprehensive use of available information and does not require manual adjustment of threshold values. Moreover, an effective weight adjustment function is proposed to alleviate the diversity loss and pre-mature convergence problem in particle swarm optimization. The proposed weight function ensures particles to search thoroughly in the frame before convergence to an optimum solution. In the existence of multiple objects with similar feature composition, this algorithm is tested to significantly reduce convergence to nearby distractions compared to the other existing swarm intelligence based object trackers.