• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.167-171
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• 2007

본 논문은 패턴 분류 문제에 사용되는 퍼지 최대-최소 신경망 방법을 이용하여 특정 집합으로부터 새로운 특정 집합을 추출해내고 추출된 특정 집합으로부터 의미 있는 특정을 선택해 내는 새로운 방법을 제안한다. 퍼지 최대-최소 신경망은 패턴 분류를 위해 주로 사용이 되어 왔지만, 퍼지 최대-최소 신경망을 이용해 특정 집합의 값들을 패턴 공간내의 초상자의 집합으로 변환하고 변환된 초상자들끼리의 인접성을 척도로 단순한 연산을 통한 빠른 특정 집합을 선택하게 된다. 마지막으로 본 논문의 특정 집합 선택 방법을 하지 근전도 신호를 이용한 보행 패턴 분류에 적용해 보고, 그 결과를 기존 여러 특정 집합 선태 방법들과 비교해 봄으로써 제안한 방법의 타당성 및 적용 가능성을 알아본다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2016.11a
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• pp.175-178
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• 2016

실내에서의 화재 등의 재난 상황에서는 비장애인과 장애인 모두 시야 확보가 어려워져 안전하게 대피하기 어려운 위험에 직면하게 된다. 본 논문에서는 시각정보 부재 시에 보행자의 다양한 장애물에 대한 회피 및 충돌상황 방지를 위한 안전 기술에 대한 연구를 수행하였다. 특히 주변의 다양한 위험 정보를 인지하기 어려운 시각 및 청각장애인들이 안전에 위협을 느낄 수 있는 복잡한 실내외 구조물과, 시시각각 변하는 주변의 장애물 환경에 대처하기 위하여 MCU를 활용한 보드에 진동 모터, 초음파, LED 센서를 장착하여 탈부착이 가능한 웨어러블(Wearable) 모듈을 제작하였다. 장애물 감지를 위한 센서부는 사용자의 상체부 전반에 장착되어 주변의 장애물들을 보다 넓은 범위로 인식하고 대처할 수 있으며, 이후 다양한 관제시스템에 활용 가능하도록 모듈과 사용자간의 인터넷 통신을 이용하여 실시간으로 시각 및 청각장애인들의 위험감지를 보호자에게 신속하게 알려줄 수 있는 시스템을 개발하여 그 가능성을 확인하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.186-190
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• 2015

Intelligent vehicle plans motion and navigate itself based on the surrounding environment perception. Hence, the precise environment recognition is an essential part of self-driving vehicle. There exist many vulnerable road users (e.g. vehicle, pedestrians) on vehicular driving environment, the vehicle must percept all the dynamic obstacles accurately for safety. In this paper, we propose an multiple vehicle tracking algorithm using microwave radar. Our proposed system includes various special features. First, exceptional radar measurement model for vehicle, concentrated on the corner, is described by mixture density network (MDN), and applied to particle filter weighting. Also, to conquer the curse of dimensionality of particle filter and estimate the time-varying number of multi-target states, reversible jump markov chain monte carlo (RJMCMC) is used to sampling step of the proposed algorithm. The robustness of the proposed algorithm is demonstrated through several computer simulations.

• Journal of the Korea Society of Computer and Information
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• v.17 no.8
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• pp.107-114
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• 2012

We have developed a textile capacitive pressure sensor for smart gait analysis. The proposed system can convert sensor signal into step counts and pressure levels by different posture. To evaluate the performance of insole type textile capacitive sensor, we measured capacitance change by increment of weights from 10 kg to 100 kg with 10 kg increment using M1 class rectangular weights (four 20 kg weights and two 10 kg weights) which have ${\pm}10%$ tolerance. The result showed non-linearity characteristic of a general capacitive pressure sensor. The test was performed according to a test protocol for four different postures (sitting, standing, standing on a left leg and standing on a right leg) and different walking speeds (1 km/h and 4 km/h). Five healthy male subjects were participated in each test. As we expected, the pressure level was changed by pressure distribution according to posture. Also, developed textile pressure sensor showed higher recognition rate (average 98.06 %) than commercial pedometer at all walking speed. Therefore, the proposed step counts and posture monitoring system using conductive textile capacitive pressure sensor proved to be a reliable and useful tool for monitoring gait parameters.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.2
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• pp.84-93
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• 2011

In order to provide the real time and proper information to the pedestrian who is using the transport connection and transfer center through data collecting and processing process, the design of the test-bed (Gimpo airport)'s communication construction and the technology of the pedestrian location tracking has been researched. The design of the communication construction should make sure that it can provide believable data to the user of the transfer center. At the same time, the location tracking should also be considered, so that the require of the communication efficiency and the location tracking efficiency can be met together. In order to make the efficient location tracking technology, the problems related to the commercial technology based real time location identification will be resolved and the new approach method was proposed and be applied and analysed to the test-bed. The wireless access points can be located in the most real-world situation which has added the characteristics of the real building to the electronic map, and through the analysis of theirs location, they can be set as the mainly necessary points for the communication construction design and the location tracking and the method to locate that points has been proposed. How to set, how to apply it to the test-bed and the examination result will be introduced in this paper.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.35-42
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• 2021

In this paper, we propose a deep learning-based person re-identification method using a three-dimensional RGB-Depth Xtion2 camera considering joint coordinates and dynamic features(velocity, acceleration). The main idea of the proposed identification methodology is to easily extract gait data such as joint coordinates, dynamic features with an RGB-D camera and automatically identify gait patterns through a self-designed one-dimensional convolutional neural network classifier(1D-ConvNet). The accuracy was measured based on the F1 Score, and the influence was measured by comparing the accuracy with the classifier model (JC) that did not consider dynamic characteristics. As a result, our proposed classifier model in the case of considering the dynamic characteristics(JCSpeed) showed about 8% higher F1-Score than JC.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.444-450
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• 2015

The accuracy of small and low cost CCD camera is insufficient to provide data for precisely tracking unmanned aerial vehicles(UAVs). This study shows how UAV can hover on a human targeted tracking object by using CCD camera rather than imprecise GPS data. To realize this, UAVs need to recognize their attitude and position in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for an UAV to estimate of his attitude by environment recognition for UAV hovering, as one of the best important problems. In this paper, we describe a method for the attitude of an UAV using image information of a maker on the floor. This method combines the observed position from GPS sensors and the estimated attitude from the images captured by a fixed camera to estimate an UAV. Using the a priori known path of an UAV in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a marker on the floor and the estimated UAV's attitude. Since the equations are based on the estimated position, the measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the UAV. The Kalman filter scheme is applied for this method. its performance is verified by the image processing results and the experiment.

• Information and Communications Magazine
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• v.32 no.12
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• pp.32-37
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• 2015

본 글에서는 철도교통의 안전성 향상을 위해 철도건널목의 지장물을 검지하는 기술을 소개한다. 철도건널목에 자동차나 보행자 등 열차운행에 지장을 줄 수 있는 물체가 존재하는지 확인하기 위하여 현재 레이저빔 방식의 검지장치를 사용하고 있으나 기술적 한계와 문제점을 보이고 있다. 이를 극복하기 위해 2차원 레이저스캐너 센서를 적용하여 새로운 지장물 검지 시스템을 설계하였으며, 관심구간에 존재하는 물체의 크기와 방향을 검지하는 알고리즘을 탑재하여 효과적인 지장물 인식이 가능하도록 하였다. 제작한 시작품을 실제 운영노선에 설치하여 현장시험을 수행하였다. 본 글에서는 개발된 기술을 설명하고 현장시험 결과를 소개하고자 한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.5
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• pp.35-49
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• 2014

This paper proposes the on-road object detection and classification algorithm by using a detection system consisting of only laser scanners. Each sensor data acquired by the laser scanner is fused with a grid map and the measurement error and spot spaces are corrected using a labeling method and dilation operation. Fuzzy method which uses the object information (length, width) as input parameters can classify the objects such as a pedestrian, bicycle and vehicle. In this way, the accuracy of the detection system is increased. Through experiments for some scenarios in the real road environment, the performance of the proposed detection and classification system for the actual objects is demonstrated through the comparison with the actual information acquired by GPS-RTK.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.323-324
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• 2022

본 논문에서는 사람의 개입 없이 실내 환경에서 마스크 미 착용자를 스스로 발견한 후 방역수칙위반 사실에 대한 경고와 함께 마스크 착용을 권고하는 인공지능 기반의 자율주행 서비스 로봇을 개발한다. 제안한 시스템에서 로봇은 동시적 위치 추적 지도 작성 기법인 SLAM(Simultaneous Localization and Mapping)기술을 이용하여 지도를 작성한 후 사용자가 제공한 웨이포인트(Waypoint)를 기반으로 자율주행한다. 또한, YOLO(You Only Look Once) 알고리즘을 이용한 실시간 객체 인식 기술을 활용하여 보행자의 마스크 착용 여부를 판단한다. 실험을 통해 사전에 작성된 지도에 지정된 웨이포인트를 따라 로봇이 자율주행하는 것을 확인하였다. 또한, 충전소로 이동할 경우, 영상 처리 기법을 활용하여 충전소에 부착된 표식에 근접하도록 이동하여 충전이 진행됨을 확인하였다.