• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.31-34
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• 2005

Mobile devices, such as PDAs, portable multimedia players, are more likely to encompass large storage devices with prevalance of high-quality multimedia contents. This paper proposes an object-based multimedia contents storage architecture that employs the object-based storage device model and the iSCSI protocol. It also provides a multimedia content player that operates directly with the proposed storage architecture. We implement both the proposed storage architecture and the multimedia content player upon the Linux environment. Performance evaluation by playing MP3 multimedia contents reveals that the proposed storage architecture reduces the total power consumption by 9%, compared with an existing networked storage. This enhancement is mainly contributed to the fact that a large portion of the file system is moved into the object-based multimedia contents storage from the mobile device.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1121-1141
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• 2020

We propose a robust visual object tracking algorithm fusing a convolutional neural network tracker trained offline from a large number of video repositories and a color histogram based tracker to track objects for mixing immersive audio. Our algorithm addresses the problem of occlusion and large movements of the CNN based GOTURN generic object tracker. The key idea is the offline training of a binary classifier with the color histogram similarity values estimated via both trackers used in this method to opt appropriate tracker for target tracking and update both trackers with the predicted bounding box position of the target to continue tracking. Furthermore, a histogram similarity constraint is applied before updating the trackers to maximize the tracking accuracy. Finally, we compute the depth(z) of the target object by one of the prominent unsupervised monocular depth estimation algorithms to ensure the necessary 3D position of the tracked object to mix the immersive audio into that object. Our proposed algorithm demonstrates about 2% improved accuracy over the outperforming GOTURN algorithm in the existing VOT2014 tracking benchmark. Additionally, our tracker also works well to track multiple objects utilizing the concept of single object tracker but no demonstrations on any MOT benchmark.

• Journal of the Korea Society of Computer and Information
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• v.25 no.1
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• pp.45-53
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• 2020

Conventional Convolutional Neural Network(CNN) algorithms have limitations in detecting small objects in large image. In this paper, we propose an improved model which is based on Region Of Interest(ROI) selection and image dividing technique. We prepared YOLOv3 / Faster R-CNN algorithms which are transfer-learned by airfield and aircraft datasets. Also we prepared large images for testing. In order to verify our model, we selected airfield area from large image as ROI first and divided it in two power n orders. Then we compared the aircraft detection rates by number of divisions. We could get the best size of divided image pieces for efficient small object detection derived from the comparison of aircraft detection rates. As a result, we could verify that the improved CNN algorithm can detect small object in large images.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.307-310
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• 2000

The measuring method of large object using the pattern matching is discussed in the paper. It is hard and expensive to get the complete 3D data when the object is large or exceeds the limit of measuring devices. The large object is divided into several smaller areas and is scanned several times to get the data of all the pieces. These data are aligned to get the complete 3D data using the pattern matching method. The point pattern matching method and transform matrix algorithm are used for aligning. The laser slit beam and CCD camera is applied for experimental measurement. Visual C++ on Window98 is implemented in processing the algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.9
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• pp.714-719
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• 2003

We propose a measuring method of large object using the pattern matching. It is hard and expensive to get the complete 3D data when the object is large and exceeds the limit of measuring devices. The large object is divided into several smaller areas and is scanned several times to get the data of all the pieces. These data are aligned to get the complete 3D data using the pattern matching method such as point pattern matching method and transform matrix algorithm. The laser slit beam and CCD camera are applied for the experimental measurement. Visual C＋＋ on Windows 98 is implemented in processing the algorithm.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.567-574
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• 2013

In this paper, we have proposed an architectural solution for a system for the visualization and modification of large amounts of data. The pattern is based on an asynchronous execution of programmable commands and a reflective approach of an object structure composition. The described pattern provides great flexibility, which helps adopting it easily to custom application needs. We have implemented a system based on the described pattern. The implemented system presents an innovative approach for a dynamic data object initialization and a flexible system for asynchronous interaction with data sources. We believe that this system can help software developers increase the quality and the production speed of their software products.

• Korean Journal of Computational Design and Engineering
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• v.19 no.3
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• pp.294-304
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• 2014

This paper presents a real-time rendering algorithm of large-scale geometric data using GLSL (OpenGL shading language). It details the VAO (vertex array object) and VBO(vertex buffer object) to be used for up-loading the large-scale point clouds and polygon meshes to a graphic video memory, and describes the shader program composed by a vertex shader and a fragment shader, which manipulates those large-scale data to be rendered by GPU. In addition, we explain the global rendering procedure that creates and runs the shader program with the VAO and VBO. Finally, a rendering performance will be measured with application examples, from which it will be demonstrated that the proposed algorithm enables a real-time rendering of large amount of geometric data, almost impossible to carry out by previous techniques.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.522-525
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• 1995

A manipulation of a multiple contacted object by a Rotational Base and Single-jointed Finger mechanism(RBSF mechanism) is discussed. The manipulation is characterized by multiple contacts on an object and large motions of the object with sliding contacts. The kinematics and dynamics allowing sliding at multiple contacts are explored. The conditions for manipulation of an object at multiple contacts by the RBSF mechanism, which cannot exert arbitrary contact forces because it has a fewer number of joints than is required for active control, is presented.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.233-236
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• 1998

In this paper, we present a novel approach named a shared library as an active memory object for application software development of large-scale real-time systems. Unlike the general passive shared memory, shared library proposed in this paper can be activated as an execution object. Moreover this is not tightly coupled with application programs unlike the normal libraries. To implement this mechanism, operating system makes the shared memory as an active object and shared library realizes the indirect call structure. This mechanism enhanced the utilization of main memory and communication performance. And this is successfully applied to the HANbit ACE ATM switching system and the TDX-10 switching system.

• Journal of Information Technology Applications and Management
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• v.15 no.2
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• pp.1-14
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• 2008

The distinguished prosperity of information technologies from great progress of e-business during the last decade has unavoidably made software development for active data mining to discovery hidden predictive information regarding business trends and behavior from vary large databases. Therefore this paper develops an active mining object(ADMO) component, which provides real-time predictive information from web databases. The ADMO component is to extended ADO(ActiveX Data Object) component to active data mining component based on COM(Component Object Model) for application program interface(API). ADMO component development made use of window script component(WSC) based on XML(eXtensible Markup Language). For the purpose of investigating the application environments and the practical schemes of the ADMO component, experiments for diverse practical applications were performed in this paper. As a result, ADMO component confirmed that it could effectively extract the analytic information of classification and aggregation from vary large databases for Web services.