• Smart Media Journal
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• v.12 no.7
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• pp.18-26
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• 2023

In this study, we propose a cow behavior recognition system based on YOLOX and OC-SORT. YOLO X detects targets in real-time and provides information on cow location and behavior. The OC-SORT module tracks cows in the video and assigns unique IDs. The quantitative analysis module analyzes the behavior and location information of cows. Experimental results show that our system demonstrates high accuracy and precision in target detection and tracking. The average precision (AP) of YOLOX was 82.2%, the average recall (AR) was 85.5%, the number of parameters was 54.15M, and the computation was 194.16GFLOPs. OC-SORT was able to maintain high-precision real-time target tracking in complex environments and occlusion situations. By analyzing changes in cow movement and frequency of mounting behavior, our system can help more accurately discern the estrus behavior of cows.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.563-570
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• 2024

This paper proposes a method to recognize and track drivable lane areas to assist the driver. The main topic is designing a deep-based network that predicts drivable road areas using computer vision and deep learning technology based on images acquired in real time through a camera installed in the center of the windshield inside the vehicle. This study aims to develop a new model trained with data directly obtained from cameras using the YOLO algorithm. It is expected to play a role in assisting the driver's driving by visualizing the exact location of the vehicle on the actual road consistent with the actual image and displaying and tracking the drivable lane area. As a result of the experiment, it was possible to track the drivable road area in most cases, but in bad weather such as heavy rain at night, there were cases where lanes were not accurately recognized, so improvement in model performance is needed to solve this problem.

• Korean Journal of Construction Engineering and Management
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• v.12 no.2
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• pp.12-20
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• 2011

Recently, construction site scale has been growing larger along with the growth of national economy. As construction market requires time reduction, cost saving, and improving quality, a cutting-edge technology applied research has been gradually studied for more efficient project management. In particular, the Real Time Location System (RTLS) technology, a real-time location tracking system of construction resources, can be effectively used in safety management. This technology has been studied and applied in various industries including architectural, marine, urban, and other industries. However, although tunnel construction in civil engineering has a narrow space and many safety risks, there are not researched about this content. Therefore, this study proposes an advanced safety management model for tunnel construction using the RTLS technology and a measurement method of the feasibility of this model in the construction site.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.1B
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• pp.86-97
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• 2009

RTLS is a system for automatically locating and tracking people and objects. The TDOA-based RTLS determines the location of the tag by calculating the time differences of a signal received from the tag. In TDOA-based RTLS, time synchronization is essential to calculate the time difference between readers. This paper presents a precision time synchronization method for TDOA-based RTLS over IEEE 802.15.4. In order to achieve precision time synchronization in IEEE 802.15.4 radio, we analyzed the error factors of delay and jitter. We also deal with the implementation of hardware assisted time stamping and the Kalman filtering method to minimize the error factors. In addition, this paper described the experiments and performance evaluation of the proposed precision time synchronization method in IEEE 802.15.4 radio. The results show that the nodes in a network can maintain their clocks to within 10 nanoseconds offset from the reference clock.

• Journal of KIISE:Software and Applications
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• v.30 no.12
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• pp.1228-1238
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• 2003

This paper presents a new and practical method based on computer vision for detecting the monitor position where the user is looking. In general, the user tends to move both his face and eyes in order to gaze at certain monitor position. Previous researches use only one wide view camera, which can capture a whole user's face. In such a case, the image resolution is too low and the fine movements of user's eye cannot be exactly detected. So, we implement the gaze detection system with dual camera systems(a wide and a narrow view camera). In order to locate the user's eye position accurately, the narrow view camera has the functionalities of auto focusing and auto panning/tilting based on the detected 3D facial feature positions from the wide view camera. In addition, we use dual R-LED illuminators in order to detect facial features and especially eye features. As experimental results, we can implement the real-time gaze detection system and the gaze position accuracy between the computed positions and the real ones is about 3.44 cm of RMS error.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.49-55
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• 2021

Recently, a small tracking radar requires the development of a small millimeter wave tracking radar having a high range resolution that can acquire and track a target in various environments and disable the target system with a single blow. Small millimeter wave tracking radar with high range resolution needs to implement a signal processor that can process wide bandwidth signals in real time and meet the requirements of small tracking radar. In this paper, we designed a signal processor that can perform the role and function of a signal processor for a small millimeter wave tracking radar. The signal processor for the small millimeter wave tracking radar requires the real-time processing of input signal of OOOMHz center frequency and OOOMHz bandwidth from 8 channels. In order to satisfy the requirements of the signal processor, the signal processor was designed by applying the high-performance FPGA (Field Programmable Gate Array) and ADC (Analog-to-digital converter) for pre-processing operations, such as DDC (Digital Down Converter) and FFT (Fast Fourier Transform). Finally, the signal processor of the small millimeter wave tracking radar was verified via performance test.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.2
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• pp.149-157
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• 2009

Tracking technologies which provide real-time and customized information through various information collecting and processing for pedestrians who use traffic connective and transferring center have been being examined. However some problems are caused due to the wide-range positioning error for some services as device installation and service place. It is also difficult to be applied to traffic linkage and transfer services because many situations can be barren. In the testbed, Gwangmyoung Station, we got some results in bad conditions such as a lot of steel construction and another communication device. Practically, conditions of the place which will be built can be worse than Gwangmyoung station. Therefore, we researched suitable Location correction algorithm as a method for accuracy to traffic connective and transferring system. And its algorithm is designed through grid coordinates, map-matching, modeling coordinates and Kalman filtering and is being implemented continuously. Also preparing for optimization of various transferring center model, we designed for simulator type algorithm what is available for deciding algorithm factor.

• Journal of Internet Computing and Services
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• v.4 no.4
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• pp.9-14
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• 2003

A GUI (graphical user interface) has been a dominant platform for HCI (human computer interaction). A GUI - based interaction has made computers simpler and easier to use. The GUI - based interaction, however, does not easily support the range of interaction necessary to meet users' needs that are natural. intuitive, and adaptive. In this paper, the modified BMA (block matching algorithm) is proposed to track a hand in a sequence of an image and to recognize it in each video frame in order to replace a mouse with a pointing device for a virtual reality. The HCI system with 30 frames per second is realized in this paper. The modified BMA is proposed to estimate a position of the hand and segmentation with an orientation of motion and a color distribution of the hand region for real - time processing. The experimental result shows that the modified BMA with the YCbCr (luminance Y, component blue, component red) color coordinate guarantees the real - time processing and the recognition rate. The hand tracking by the modified BMA can be applied to a virtual reclity or a game or an HCI system for the disable.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06d
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• pp.316-318
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• 2006

본 논문에서는 차세대 지능형 교통시스템인 UTIS(Urban Traffic Information System)의 빠른 접속 요구 조건을 만족하기 위한 DLC(Dynamic Limited Contention) 알고리즘을 제안한다. UTIS 네트워크는 고속으로 이동하는 차량에 설치된 모바일 노드와 도로 변에 설치된 노변 기지국으로 구성되며, 이 네트워크를 통해서 IP 데이터 그램의 전송 서비스, 방송 데이터를 실시간으로 전송하는 실시간 전송 서비스 그리고 차량의 위치를 계속적으로 알려 주는 위치 탐색 서비스를 지원한다. 이러한 전송 서비스를 지원하기 위해서 UTIS는 물리 계층과 MAC 계층으로 구성된다. 그러나 UTIS에서는 차량의 고속 이동으로 인해서 셀(cell)간의 핸드오프가 빈번히 발생하고 또한 위치 추적과 방송 서비스와 같은 실시간 전송 서비스를 지원해야 하기 때문에 기존의 802.11 MAC을 사용할 수 없다. 즉 UTIS에서의 빠른 등록 요구 조건을 충족시키기 위해 기존의 802.11에서 사용하는 경쟁(contention) 방식은 비효율적이다. 본 논문에서는 셀 내에 도착하는 노드 수에 따라 경쟁을 하는 그룹의 크기를 동적으로 조절하는 DLC 알고리즘을 제안한다. 기존의 UTIS에서는 그룹 크기를 정적으로 결정하고 모바일 노드는 자신의 주소에 이 정적 그룹 크기로 modulo하여 자신의 속한 그룹을 초기에 계산한다. 기지국이 접속해야하는 그룹을 폴링 메시지로 지정할 때 그 그룹에 속한 모바일 노드들만이 제한적으로 경쟁하게 된다. 이러한 정적인 그룹 크기는 셀 내에의 노드의 숫자와 그룹 크기의 분포를 고려하지 않는 방식으로 비효율적이다. 본 DLC 알고리즘에서는 전 폴링 주기 동안에 경쟁하는 노드의 빈도수를 계속적으로 추적하여 등록 시점에 경쟁하는 그룹의 개수를 동적으로 조절하게 된다. 이러한 방식은 UTIS와 같이 접속 시간이 제한적이고 접속하려는 노드 수가 빠르게 변화하는 환경 하에서 기존의 802.11 MAC 프로토콜과 정적인 그룹 크기 방식에 비해 효율적이다.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.19-28
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• 2022

In this paper, we propose the Detector Scheduler which determines the best tracking-by-detection (TBD) mechanism to perform real-time high-accurate multi-object tracking (MOT). The Detector Scheduler determines whether to run a detector by measuring the dissimilarity of features between different frames. Furthermore, we propose a self-supervision method to learn the Detector Scheduler with tracking results since it is difficult to generate ground truth (GT) for learning the Detector Scheduler. Our proposed self-supervision method generates pseudo labels on whether to run a detector when the dissimilarity of the object cardinality or appearance between frames increases. To this end, we propose the Detector Scheduling Loss to learn the Detector Scheduler. As a result, our proposed method achieves real-time high-accurate multi-object tracking by boosting the overall tracking speed while keeping the tracking accuracy at most.