• Journal of Korea Multimedia Society
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• v.12 no.12
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• pp.1728-1735
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• 2009

Human action tracking plays an important place in human-computer-interaction, human action tracking is a challenging task because of the exponentially increased computational complexity in terms of the degrees of freedom of the object and the severe image ambiguities incurred by frequent self-occlusions. In this paper, we will propose a novel method to track human action, in our technique, a dynamic background estimation algorithm will be applied firstly. Based on the estimated background, we then extract the human object from the video sequence, and the skeletonization method and Hough transform method will be used to detect the main structure of human body and each part rotation angle. The calculated rotation angles will be used to control a crane in the port, thus we can just control the container crane by using signalman body. And the experimental results can show that our proposed method can get a preferable result than the conventional methods such as: MIT, JPF or MFMC.

• Journal of Korea Multimedia Society
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• v.22 no.2
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• pp.128-135
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• 2019

This paper presents a deep learning-based object detection method for recognizing vehicles in images acquired through cameras installed on ceiling of underground parking lot. First, we present an image enhancement method, which improves vehicle detection performance under dark lighting environment. Second, we present a new CNN-based multiscale classifiers for detecting vehicles in images acquired through cameras with fisheye lens. Experiments show that the presented vehicle detector has better performance than the conventional ones.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.1017-1028
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• 2019

Pedestrian tracking is a particular object tracking problem and an important component in various vision-based applications, such as autonomous cars and surveillance systems. Following several years of development, pedestrian tracking in videos remains challenging, owing to the diversity of object appearances and surrounding environments. In this research, we proposed a tracking-by-detection system for pedestrian tracking, which incorporates a convolutional neural network (CNN) and color information. Pedestrians in video frames are localized using a CNN-based algorithm, and then detected pedestrians are assigned to their corresponding tracklets based on similarities between color distributions. The experimental results show that our system is able to overcome various difficulties to produce highly accurate tracking results.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.47-54
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• 2019

This study is concerned with the mechanism and structure of an optical microscope and an automatic multi-focus algorithm for automatically selecting sharp images from multiple foci of a cell. To obtain precise cell images quickly, a z-axis actuator with a resolution of $0.1{\mu}m$ was designed to control an optical microscope Moreover, a lighting control system was constructed to select the color and brightness of light that best suit the object being viewed. Cell images are captured by the instrument and the sharpness of each image is determined using Gaussian and Laplacian filters. Next, cubic spline interpolation and peak detection algorithms are applied to automatically find the most vivid points among multiple images of a single object. A cancer cell imaging experiment using propidium iodide staining confirmed that a sharp multipoint image can be obtained using this microscope. The proposed system is expected to save time and effort required to extract suitable cell images and increase the convenience of cell analysis.

• Journal of Korea Game Society
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• v.21 no.1
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• pp.91-98
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• 2021

In this paper, we propose the system that simultaneously controls objects in virtual reality and objects in real environments using brain waves. We propose a system that measures brain waves to grasp the user's concentration and quantifies them to raise or lower virtual and real objects. We implemented a web-based virtual reality system and an embedded system based on a raspberry pi for test of design. It was confirmed that the control of virtual and real objects is possible using BCI. The result was that it was possible to develop various contents using this.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.46.3-46.3
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• 2019

We present the control software and its development process for a prototype of the Camera and Grating Articulation System (CGAS) for GMACS, a wide-field, multi-object, moderate-resolution optical spectrograph for the Giant Magellan Telescope (GMT). The CGAS prototype is currently designed for the camera articulation controller as a miniature model of the GMACS. The camera articulation package (CAP) is a software that controls two stepper motors to adjust the camera angle. The package is developed using Visual C++ and runs on Windows 10. We discuss the architectural design and communication route between the high-end user software and the electronics hardware.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.2
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• pp.164-172
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• 2014

Recently, as the number of IoT (Internet of Things) devices for personal or home intelligence increases, the need for unified control and cooperative utilization is required. This paper presents a novel idea, proposes methods for virtualizing Internet of Things (IoT) devices and hosting them on the home AP instead of relying on a cloud service or purchasing a new device to do so. For this, the process and profile of the IoT gadgets need to be virtualized into JavaScript-based objects. Then, to execute and control the instances of the virtualized IoT objects on the wireless AP, a novel instance management method and their interfaces are designed. The implementation and performance section demonstrates the proposed system's stability and operability by showing the stress test results while the wireless AP is running for its wireless routing.

• The Journal of Korean Association of Computer Education
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• v.8 no.1
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• pp.73-80
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• 2005

To achieve a natural and plausible interaction with deformable objects and to setup the desirable initial conditions of simulation, user should be able to define and control the geometric constraints intuitively. In addition, user should be able to utilize the simulation as a problem solving platform by experimenting various simulation situations without major modification of the simulator. The proposed physically based geometric constraint simulation system solves the problem using a non-linear finite element method approach to represent deformable objects and constraint forces are generated by defining geometric constraints on the nodes of the object to maintain the restriction. It allows user to define and modify geometric constraints and an algorithm converts these geometric constraints into constraint forces which seamlessly integrate controllability to the simulation system. Simulator can handle linear, angular, inequality based geometric constraints on the objects. Our experimental results show that constraints are maintained in the tight error bound and preserve desired shape of deformable object during the entire simulation.

• Journal of KIISE:Information Networking
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• v.30 no.2
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• pp.260-269
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• 2003

The traditional distributed object middleware platform is not suitable for the transmission of stream data, because RPC(Remote Procedure Call)-based message transmission have a great overhead. Therefore, the OMG(Object Management Group) proposes the AV(Audio and Video) stream reference model for streaming on the distributed object middleware platform. But, this reference model has not a detail of implementation. Particularly it also has not congestion control scheme for improvement of network efficiency on the real network environment. It is a very important and difficult technical issue to provide the stream transmission platform with advanced congestion control scheme. In this paper, we propose an architecture of a distributed stream transport platform and deal with the design and implementation concept of our proposed platform. Also, we present a mechanism to improve streaming utilization by SRTP(Smart RTP). SRTP is our proposed TCP-Friendly scheme.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.1
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• pp.47-56
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• 2004

This paper describes a new bit allocation algorithm that can achieve a constant bit rate when coding multiple video objects, while improving rate-distortion (R-D) performance over the VM5 method for MPEG-4 object-based video coding. In particular, we propose two models to estimate the rate-distortion characteristics of coded objects as well as skipped objects. Based on the proposed models, we present several R-D coding modes with spatio-temporal trade-offs to improve coding efficiency. The proposed algorithm is performed at the object level for object-based video coding. Simulation results demonstrate moderate improvement at low as well as high bit rates. The proposed algorithm can produce the actual coded bits very close to the target bits over a wide range of bit rates. Consequently, the proposed algerian has not experienced any buffer overflow or underflow over the bit rates between 32 kbps and 256 kbps.