• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.481-490
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• 2013

In this paper, an investigation of weapon tracking performance is shown in regard to improving individual weapon performance of aiming objects. On the battlefield, a battle can last only a few hours, sometimes it can last several days until finished. In these long-lasting combats, a wide variety of factors will gradually lower the visual ability of soldiers. The experiments were focusing on enhancing the degraded aiming performance by applying visual tracking technology to roof mounted sights so as to track the movement of troops automatically. In order to select the optimal algorithm among the latest visual tracking techniques, performance of each algorithm was evaluated using the real combat images with characteristics of overlapping problems, camera's mobility, size changes, low contrast images, and illumination changes. The results show that VTD (Visual Tracking Decomposition)[2], IVT (Incremental learning for robust Visual Tracking)[7], and MIL (Multiple Instance Learning)[1] perform the best at accuracy, response speed, and total performance, respectively. The evaluation suggests that the roof mounted sights equipped with visual tracking technology are likely to improve the reduced aiming ability of forces.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.201-211
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• 2013

In this paper, we propose a hand tracking and gesture recognition system. Our system employs a depth capture device to obtain 3D geometric information of user's bare hand. In particular, we build a flexible tracking volume and restrict the hand tracking area, so that we can avoid diverse problems caused by conventional object detection/tracking systems. The proposed system computes running average of the hand position, and tracking volume is actively adjusted according to the statistical information that is computed on the basis of uncertainty of the user's hand motion in the 3D space. Once the position of user's hand is obtained, then the system attempts to detect stretched fingers to recognize finger gesture of the user's hand. In order to test the proposed framework, we built a NUI system using the proposed technique, and verified that our system presents very stable performance even in the case that multiple objects exist simultaneously in the crowded environment, as well as in the situation that the scene is occluded temporarily. We also verified that our system ensures running speed of 24-30 frames per second throughout the experiments.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.7
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• pp.754-759
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• 2015

Nowadays, short distance communication systems with low power energy (LPE) are developed for identification and monitoring of site identification of vessel crews and passengers (SIVCP). LPE communication modules, such as Bluetooth low energy (BLE) and Zigbee, are used for short distance communications with LPE. These modules enable 1:N communications and their popularity is growing since the modules can be mounted on movable objects, such as mobile devices and human body. When these modules are used, the important factor that affects their operation time and design are the capacity and size of battery. Therefore, they must be made as small as possible, and the battery should be selected to be slightly smaller than the module. In this study, we calculate the theoretical life of batteries used in SIVCP BLE modules using data sheet and discharge characteristic graph under the condition of a 1/250 transmission-ratio (TR). We thus calculate experimental life by measuring transmission current for the same TR, and low speed mode current for a 1/5000 TR and measure long-term experimental life using 1/25 TR for days. Through these experiments, we verify experimental methods for the prediction and extension of battery life that would enable us to select appropriate sizes of batteries based on vessel usage and passenger types. The selections of the module TR and battery size are important factors affecting the cost reduction of module design, the battery maintenance, and passenger convenience.

• Journal of Broadcast Engineering
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• v.16 no.2
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• pp.350-359
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• 2011

Fast developments of broadcasting technologies since 1990s enabled not only High Definition Television service providing high quality audiovisual contents at home but also mobile broadcasting service providing audiovisual contents to high speed moving vehicle. Terrestrial Digital Multimedia Broadcasting (T-DMB) is one of the technologies developed for mobile broadcasting service, which has been successfully commercialized. One of the major technical breakthroughs achieved by T-DMB in addition to robust vehicular reception is an adoption of framework based on MPEG-4 System. It naturally enables integrated interactive data services by using Binary Format for Scene (BIFS) technology for scene description and representation of graphics object and Object Descriptor Framework representing multimedia service components as objects. T-DMB interactive data service has two fundamental limitations. Firstly, graphic data for interactive service should be always overlaid on top of a video not to be rendered out of it. Secondly, data for interactive service is only received by broadcasting channel. These limitations were considered as general in broadcasting systems. However, they are being considered as hard limitations for personalized data services using location information and user characteristics which are becoming widely used for data services of smart devices in these days. In this paper, the architecture of T-DMB hybrid data service is proposed which is utilizing broadcasting network, wireless internet and local storage for delivering BIFS data to overcome these limitations. This paper also presents hybrid BIFS technology to implement T-DMB hybrid data service while maintaining backward compatibility with legacy T-DMB players.

• The KIPS Transactions:PartD
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• v.15D no.6
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• pp.861-872
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• 2008

As rapid development of computing environment, field of automatic identification research which interoperates with various physical objects and digital information is making active progress. Although the automatic identification system is widely used in various industries, application of automatic identification system in the field of medical health doesn't reach other industry. Therefore research in medical health supplies such as medical equipment, blood, human tissues and etc is on progress. This paper suggests the application of automatic identification technology for biological resources which is core research material in human genome research. First of all, user environment requirements for the introduction of automatic identification technology are defined and through the experiments and research, barcode is selected as a suitable tag interface. Data Matrix which is 2D barcode symbology is chosen and data schema is designed based on UCC/EAN-128 for international defecto standard. To showapplicability of proposed method when applied to actual environment, we developed, tested and evaluated application as following methods. Experiments of barcode read time at 196 and 75 below zero which is actual temperature where biological resources are preserved resulted read speed of average of 1.6 second and the data schema satisfies requirements for the biological resources application. Therefore suggested method can provide data reliability as well as rapid input of data in biological resources information processing.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.2
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• pp.133-140
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• 2017

In this paper, we has proposed an automatic vehicle monitoring system based on computer vision technology. The real-time display system has displayed a system that can be performed in automatic monitoring and control while meeting the essential requirements of ITS. Another advantage has that for a powerful vehicle tracking, the main obstacle handing system, which has the shadow tracking of moving objects. In order to obtain all kinds of information from the tracked vehicle image, the vehicle must be clearly displayed on the surveillance screen. Over time, it's necessary to precisely control the vehicle, and a three-dimensional model-based approach has been also necessary. In general, each type of vehicle has represented by the skeleton of the object or wire frame model, and the trajectory of the vehicle can be measured with high precision in a 3D-based manner even if the system has not running in real time. In this paper, we has applied on segmentation method to vehicle, background, and shadow. The validity of the low level vehicle control tracker was also detected through speed tracking of the speeding car. In conclusion, we intended to improve the improved tracking method in the tracking control system and to develop the highway monitoring and control system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.3
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• pp.141-148
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• 2021

This paper presents a method to detect zebra-crossing using deep learning which combines SegNet and ResNet. For the blind, a safe crossing system is important to know exactly where the zebra-crossings are. Zebra-crossing detection by deep learning can be a good solution to this problem and robotic vision-based assistive technologies sprung up over the past few years, which focused on specific scene objects using monocular detectors. These traditional methods have achieved significant results with relatively long processing times, and enhanced the zebra-crossing perception to a large extent. However, running all detectors jointly incurs a long latency and becomes computationally prohibitive on wearable embedded systems. In this paper, we propose a model for fast and stable segmentation of zebra-crossing from captured images. The model is improved based on a combination of SegNet and ResNet and consists of three steps. First, the input image is subsampled to extract image features and the convolutional neural network of ResNet is modified to make it the new encoder. Second, through the SegNet original up-sampling network, the abstract features are restored to the original image size. Finally, the method classifies all pixels and calculates the accuracy of each pixel. The experimental results prove the efficiency of the modified semantic segmentation algorithm with a relatively high computing speed.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.4
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• pp.125-132
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• 2021

As the layers of artificial neural network deepens, and the dimension of data used as an input increases, there is a problem of high arithmetic operation requiring a lot of arithmetic operation at a high speed in the learning and recognition of the neural network (NN). Thus, this study proposes a data dimensionality reduction method to reduce the dimension of the input data in the NN. The proposed Line-segment Feature Analysis (LFA) algorithm applies a gradient-based edge detection algorithm using median filters to analyze the line-segment features of the objects existing in an image. Concerning the extracted edge image, the eigenvalues corresponding to eight kinds of line-segment are calculated, using 3×3 or 5×5-sized detection filters consisting of the coefficient values, including [0, 1, 2, 4, 8, 16, 32, 64, and 128]. Two one-dimensional 256-sized data are produced, accumulating the same response values from the eigenvalue calculated with each detection filter, and the two data elements are added up. Two LFA256 data are merged to produce 512-sized LAF512 data. For the performance evaluation of the proposed LFA algorithm to reduce the data dimension for the recognition of handwritten numbers, as a result of a comparative experiment, using the PCA technique and AlexNet model, LFA256 and LFA512 showed a recognition performance respectively of 98.7% and 99%.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.1
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• pp.40-47
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• 2009

This paper presents the method of measuring the feedback interference channel, which is developed between the transmit and receive antennas of a wireless repeater by receiving the transmit signal at the receive antenna of the identical repeater, and experiment results obtained by analyzing the measurements. This experiment uses 2 GHz WCDMA signal and is carried out near a highway. The high-speed mobiles on highways cause reflected signals with high Doppler frequencies and large energy. In order to characterize the feedback channel, the power delay profile and the scattering function are estimated by identifying the delay spread, the Doppler spread, the number of fingers, and the attenuation with delay. Since the feedback interference channel is constructed between the fixed TX and RX antennas, which is dependent upon the multipaths developed by moving or fixed objects around the antennas, the channel shows different properties comparing to the conventional channels between the base station and the mobile station. Therefore, the results presented in the paper are expected to provide guidelines for designing and evaluating wireless repeater systems.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1275-1288
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• 2015

A microscale weather analysis module (about 1km or less) is a microscale numerical weather prediction model designed for operational forecasting and atmospheric research needs such as radiant energy, thermal energy, and humidity. The accuracy of the module is directly related to the usefulness and quality of real-time microscale weather information service in the metropolitan area. This paper suggests an object based verification method useful for spatio-temporal evaluation of the accuracy of the microscale weather analysis module. The method is a graphical method comprised of three steps that constructs a lattice field of evaluation statistics, merges and identifies objects, and evaluates the accuracy of the module. We develop lattice fields using various evaluation spatio-temporal statistics as well as an efficient object identification algorithm that conducts convolution, masking, and merging operations to the lattice fields. A real data application demonstrates the utility of the verification method.