• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.141-152
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• 2011

Growing efforts and interests of security techniques in a diverse surveillance environment, the intelligent surveillance system, which is capable of automatically detecting and tracking target objects in multi-cameras environment, is actively developing in a security community. In this paper, we propose an effective visual surveillance system that is avaliable to track objects continuously in multiple non-overlapped cameras. The proposed object tracking scheme consists of object tracking module and tracking management module, which are based on hand-off scheme and protocol. The object tracking module, runs on IP camera, provides object tracking information generation, object tracking information distribution and similarity comparison function. On the other hand, the tracking management module, runs on video control server, provides realtime object tracking reception, object tracking information retrieval and IP camera control functions. The proposed object tracking scheme allows comprehensive framework that can be used in a diverse range of application, because it doesn't rely on the particular surveillance system or object tracking techniques.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.6
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• pp.148-155
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• 2008

This study presents a process control of the wafer edge exposure (WEE) used in 300[mm] wafer environment. WEE, as a key module of the overall track system (coater and developer) for making patterns on wafer, is a system to expose the UV-ray on the wafer to remove a photo resist around edge of the wafer. It can measure, memorize and control the distance and angles from wafer center to edge. Recently in the 300[mm] semiconductor fabrication, the track system strongly requires that WEE station has a controller with high throughput and accuracy to increase process efficiency. We have designed and developed the controller, and present here a WEE control algorithm and experimental results.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.4
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• pp.337-345
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• 2020

In this paper, an efficient signal tracking method to simultaneously track both GPS L1 C/A and Galileo E1B CBOC(6,1,1/11) using a low cost GPU is proposed. In the existing method that each GNSS signal is processed within 1 ms, more than 2 ms processing time is required in GPU to process 4 ms CBOC signal. It means that real time operation is possible if only Galileo E1B CBOC signal is concerned. But when both GPS C/A and Galileo CBOC is required, it cannot process GPS C/A signal in real time. To process 1 ms GPS C/A and 4 ms Galileo CBOC signal in real time, 4 ms Galileo CBOC signal is divided into 4 by 1 ms signal block in the proposed method. Specially, a buffer that simultaneously manages 1 ms and 4 ms signals is designed. In addition, a module that accumulates the 1 ms correlation value of the Galileo CBOC by 4 ms and passes it to the PLL and DLL is implemented. The operation and performance are evaluated with real measurements in the GPU based SDR. The experimental results show that tracking of more than 16 satellites of GPS C/A and Galileo E1B is possible using the proposed method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.6
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• pp.599-607
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• 2011

In this paper, a reaction-force compensation system for an XY linear motion stage, without an additional external isolation structure or extra motors, is developed. This system consists of a movable magnet track, a spring, a dummy weight, and a dedicated sensor module that measures the relative positions of the movable magnet track with respect to the motor coil. The reaction force compensation system is modeled, and simulations are carried out to optimize design parameters such as the moving distance of the magnet track, the transmission force, the dummy weight, and the allowed size of the mechanism. An XY linear motion stage is built, incorporating the reaction force compensation system, and the performance of the system is verified experimentally. For acceleration and deceleration values of 10 m/$s^2$, 85% of the reaction force is absorbed by the reaction force compensation system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.9-14
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• 2019

A small millimeter-wave tracking radar is a pulse-based radar that searches, detects, and tracks a target in real time through a TWS (Track While Scan) method for a traps target on the sea with a large RCS running at low speed. It is necessary to develop a board equipped with a high-speed CPU to acquire and track target information through LPRF, DBS, and HRR signal processing techniques for a trap target operating various kinds of dexterous objects such as chaff and decoy, We designed a signal processor structure including DFT (Discrete Fourier Transform) module design that can perform real - time FFT operation using FPGA (Field Programmable Gate Array) and verified the signal processor implemented through performance test.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.115-122
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• 2024

Multi-object tracking (MOT) is a vital component in understanding the surrounding environments. Previous research has demonstrated that MOT can successfully detect and track surrounding objects. Nonetheless, inaccurate classification of the tracking objects remains a challenge that needs to be solved. When an object approaching from a distance is recognized, not only detection and tracking but also classification to determine the level of risk must be performed. However, considering the erroneous classification results obtained from the detection as the track class can lead to performance degradation problems. In this paper, we discuss the limitations of classification in tracking under the classification uncertainty of the detector. To address this problem, a class update module is proposed, which leverages the class uncertainty estimation of the detector to mitigate the classification error of the tracker. We evaluated our approach on the VisDrone-MOT2021 dataset,which includes multi-class and uncertain far-distance object tracking. We show that our method has low certainty at a distant object, and quickly classifies the class as the object approaches and the level of certainty increases.In this manner, our method outperforms previous approaches across different detectors. In particular, the You Only Look Once (YOLO)v8 detector shows a notable enhancement of 4.33 multi-object tracking accuracy (MOTA) in comparison to the previous state-of-the-art method. This intuitive insight improves MOT to track approaching objects from a distance and quickly classify them.

• Journal of the Economic Geographical Society of Korea
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• v.24 no.4
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• pp.367-385
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• 2021

This study examined changes in the energy landscape, focusing on the photovoltaic module carbon certification system. As the global photovoltaic market has been reorganized around Chinese companies, the South Korean government has pushed to strengthen the competitiveness of the nation's photovoltaic industry. However, a limitation remains in that the government-led effort was not sufficient to bring about dynamic changes in the energy landscape. Against this backdrop, this study explored the stages leading to the multi-level perspectives of "macro-environment, socio-technical regime, and niche" to track the process of the government and domestic photovoltaic companies as part of a socio-technical regime responding to global market changes. In particular, this study raised an issue with the conceptual discussion of multi-level perspective, which placed a particular emphasis on the rate of change at each level and the niche in which innovative experiments take place, and thus attempted to fill this gap by tracking the energy landscape that varies differently from space. These spatial discussions can track different carbon emissions coefficients and industrial characteristics for each country, and have a higher level of explanatory power for the system thus constructed. In addition, through discussions on the problems and implications of the government-led introduction of renewable energy policies, this study suggests the need to create and implement a field-oriented system.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.394-396
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• 2006

When developing a new GPS receiver module, the essential problems are evaluation of reliable algorithms, software debugging, and performance comparison between algorithms to find optimal solution. Most GPS receiver modules nowadays use a correlator to track signals from satellites and an MCU (Micro Controller Unit) to control operations of the entire module. The problem of software evaluation from MCU is very difficult, due to limitation of MCU resources and low ability of interfacing with user. Normally, user has to expense special tool kit for a limiting access to MCU but it is also hard to use. This article introduces an implementation of a GPS receiver test bed using correlator GP2021 interfacing with ISA (Industry Standard Architecture) PC bus. This way can give user complete control and visibility into the operation of the receiver, then user can easily debug program and test algorithms. For this article, the least square method is implemented to test the hardware and software performance.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.264-264
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• 2019

The purpose of this paper is to establish development concepts for a novel collision avoidance system with preventing function of navigator's human error (Hu-CAS) in ship control behaviors. Hu-CAS consists of four modules: 1) collision risk assessment module to estimate collision priority between the ship and objects, 2) decision-making module to decide collision risk levels, 3) parameter estimation module needed in the ship control to avoid collisions and 4) control system to control the rudder angle and speed. Hu-CAS, proposed in this paper, can provide a novel system substitution current Autopilot and/or a CAS be teen manned vessel and Autonomous ship in a future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.938-958
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• 2024

Unsupervised Video Object Segmentation (UVOS) is a highly challenging problem in computer vision as the annotation of the target object in the testing video is unknown at all. The main difficulty is to effectively handle the complicated and changeable motion state of the target object and the confusion of similar background objects in video sequence. In this paper, we propose a novel deep Dual-stream Co-enhanced Network (DC-Net) for UVOS via bidirectional motion cues refinement and multi-level feature aggregation, which can fully take advantage of motion cues and effectively integrate different level features to produce high-quality segmentation mask. DC-Net is a dual-stream architecture where the two streams are co-enhanced by each other. One is a motion stream with a Motion-cues Refine Module (MRM), which learns from bidirectional optical flow images and produces fine-grained and complete distinctive motion saliency map, and the other is an appearance stream with a Multi-level Feature Aggregation Module (MFAM) and a Context Attention Module (CAM) which are designed to integrate the different level features effectively. Specifically, the motion saliency map obtained by the motion stream is fused with each stage of the decoder in the appearance stream to improve the segmentation, and in turn the segmentation loss in the appearance stream feeds back into the motion stream to enhance the motion refinement. Experimental results on three datasets (Davis2016, VideoSD, SegTrack-v2) demonstrate that DC-Net has achieved comparable results with some state-of-the-art methods.