• 패션비즈니스
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• 제11권3호
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• pp.35-45
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• 2007

This study examined how to create 2D basic pattern of individuals by means of 3-D body figure, which is to develop a flat of individual basic pattern directly from the 3-D body scan data of each subject using that of the upper body of a male adult. In terms of methodology, this study adopted 3D body scan data on system and body to make examinations in the following steps: 1. Standard point and line were set on human body, along with 3-D definition points(feature points). 2. PB was created by modifying horizontal and longitudinal section of scan data. 3. Ways to set reserve were established in the findings of PB planar development. Respective developed flat patterns were compared with pattern findings in previous studies by means of sensory evaluation. As a result, it was found that both system and body model are basic pattern and belong to appropriate pattern as semi-tight-fit basic pattern with overall appropriate tolerances. Thus, this study came to a conclusion that it is feasible and valid to develop theories for flat development as considered herein.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.230-237
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• 2022

It is difficult to predict industrial accidents in the construction industry because many accident factors, such as human-related factors and environment-related factors, affect the accidents. Many studies have analyzed the severity of injuries and types of accidents; however, there were few studies on the prediction of injured body parts. This study aims to develop a classification model to predict the part of the injured body based on accident-related factors. Construction accident cases from June 2018 to July 2021 provided by the Korea Construction Safety Management Integrated Information were collected through web crawling and then preprocessed. A naïve Bayes classifier, one of the supervised learning algorithms, was employed to construct a classification model of the injured body part, which has four categories: 1) torso, 2) upper extremity, 3) head, and 4) lower extremity. The predictor variables are accident type, type of work, facility type, injury source, and activity type. As a result, the average accuracy for each injured body part was 50.4%. The accuracy of the upper extremity and lower extremity was relatively higher than the cases of the torso and head. Unlike the other classifications, such as spam mail filtering, a naïve Bayes classifier does not provide a good classification performance in construction accidents. The reasons are discussed in the study. Based on the results of this study, more detailed guidelines for construction safety management can be provided, which help establish safety measures at the construction site.

• 한국전자파학회논문지
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• 제16권8호
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• pp.790-796
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• 2005

본 논문에서는 캡슐 내시경의 무선통신이 이루어지기 위한 환경 연구와 더불어 그에 적합한 수신 안테나를 설계하였다. 제안된 안테나는 인체와 같은 multi-loss layer환경에서 전파 손실을 최소화 하고 magnetic field를 이용하기 위해 루프 안테나로 설계했다. 주파수 대역은 인체 내 전파 손실을 고려하여 $400\~500$ MHz이고 FCC 규정에 따라 인체 각각의 조직에 대한 유전율과 도전율을 추출했다. 이를 하나의 등가 모델로 설정하고 그에 따른 유전율과 도전율을 계산해서 인체를 대신할 수 있는 수용액을 제조하였다. 전파 손실이 심한 인체 내에서 캡슐이 이동함에 따라 수신 레벨이 급격히 감소하기 때문에 배열 안테나가 요구된다. 1 mW의 신호를 송신하는 송신 안테나 위치에 상관없이 배열 안테나의 신호 레벨은 평균 -60 dBm 정도로 충분한 신호 검출이 가능한 것을 확인했다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2023년도 추계학술발표대회
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• pp.637-640
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• 2023

This paper presents multimodal image fusion with human pose for detecting abnormal human behaviors in low illumination conditions. Detecting human behaviors in low illumination conditions is challenging due to its limited visibility of the objects of interest in the scene. Multimodal image fusion simultaneously combines visual information in the visible spectrum and thermal radiation information in the long-wave infrared spectrum. We propose an abnormal event detection scheme based on the multimodal fused image and the human poses using the keypoints to characterize the action of the human body. Our method assumes that human behaviors are well correlated to body keypoints such as shoulders, elbows, wrists, hips. In detail, we extracted the human keypoint coordinates from human targets in multimodal fused videos. The coordinate values are used as inputs to train a multilayer perceptron network to classify human behaviors as normal or abnormal. Our experiment demonstrates a significant result on multimodal imaging dataset. The proposed model can capture the complex distribution pattern for both normal and abnormal behaviors.

• 한국철도학회논문집
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• 제18권3호
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• pp.194-202
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• 2015

본 연구에서는 수직 진동에 노출된 승객의 승차감을 정량적으로 분석하기 위해 점탄성 특성을 가진 시트에 기댄 인체의 동적 모델링을 제시한다. 시트 위 인체의 운동을 기술하기 위해 문헌에서 찾은 5자유도계 다물체 동역학 모델이 이용되었다. 철도차량 시트에 사용되는 점탄성 특성은 비선형 강성 특성과 시간 지연을 표현하는 컨볼루션 적분으로 수식화된다. 바닥 가진에 대한 전달함수를 분석 결과 시트의 비선형 특성으로 인해 입력 가진의 크기에 따라 전달함수는 변하는 것으로 나타났다. 측정된 철도차량의 바닥 가진을 이용하여 실제적인 인체 진동 특성을 분석한다. 주파수 가중치 자승평균치 값을 계산하고 시트 설계 파라미터가 이 주파수 가중치 자승평균치에 미치는 영향을 제시한다.

• 한국항행학회논문지
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• 제16권3호
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• pp.545-552
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• 2012

본 논문에서는 사람의 신체 일부분을 추적하는 시스템을 위해서 피부영역을 추출하고 여러 개의 영역을 추적하는 칼만 필터와 가중 탐색 영역을 이용한 다중 CAMShift 알고리즘(KWMCAMShift)을 제안한다. 배경모델을 구성하고 손과 얼굴의 피부색영역을 탐색 영역으로 하는 CAMShift를 제안한다. 이때 CAMShift의 유동적인 탐색영역을 안정화하기 위해 칼만 필터를 이용한다. 손과 얼굴 등이 상호 겹쳐지는 경우 탐색영역의 손실을 막기 위해 주 탐색영역과 비 탐색영역에 대한 가중치를 부가하여 서로 폐색 영역에 대한 회피 알고리즘을 제안한다. 얼굴 영역과 양손의 영역을 중심으로 인간의 자세를 추정하여 어깨와 손과의 관계로 팔꿈치를 추정하였고, 가우시안 배경 모델에 생성되는 그림자를 제거하여 발끝을 찾아 신체 전체를 추정하였다. 제안된 KWMCAMShift 알고리즘을 적용하였을 때 폐색 시에도 96.82%의 인식률을 보였으며 실시간이 가능하였다.

• 한국멀티미디어학회논문지
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• 제23권2호
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• pp.186-203
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• 2020

Image-based Virtual Try-On Systems are among the most potential solution for virtual fitting which tries on a target clothes into a model person image and thus have attracted considerable research efforts. In many cases, current solutions for those fails in achieving naturally looking virtual fitted image where a target clothes is transferred into the body area of a model person of any shape and pose while keeping clothes context like texture, text, logo without distortion and artifacts. In this paper, we propose a new improved image-based virtual try-on network system based on keypoints, which we name as KP-VTON. The proposed KP-VTON first detects keypoints in the target clothes and reliably predicts keypoints in the clothes of a model person image by utilizing a dense human pose estimation. Then, through TPS transformation calculated by utilizing the keypoints as control points, the warped target clothes image, which is matched into the body area for wearing the target clothes, is obtained. Finally, a new try-on module adopting Attention U-Net is applied to handle more detailed synthesis of virtual fitted image. Extensive experiments on a well-known dataset show that the proposed KP-VTON performs better the state-of-the-art virtual try-on systems.

• 한국컴퓨터정보학회논문지
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• 제9권4호
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• pp.109-116
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• 2004

본 논문은 여러 옷감 조각들을 이용하여 가상의 3차원 인체 모델에 옷을 입히기 위한 의복 시뮬레이션 시스템을 제안한다. 본 논문에서 의복은 서로 꿰매지는 2차원 재단 패턴으로 구성된다. 제안된 시스템은 3차원 인체 모델 파일과 2차원 재단 패턴 파일을 읽어 들인 다음에 질량-스프링 모델에 기반한 물리적 시뮬레이션에 의해 의복을 착용한 3D모델을 생성한다. 본 논문의 시스템은 사실적인 시뮬레이션을 위하여 인체 모델을 구성하는 삼각형과 의복을 구성하는 삼각형 사이의 충돌을 검사하고 반응 처리를 수행하였다. 인체를 구성하는 삼각형의 수가 매우 많으므로, 이러한 충돌 검사 및 반응 처리는 많은 시간을 필요로 한다. 이 문제를 해결하기 위하여, 본 논문에서는 공간 분할 기법을 이용하여 충돌 검사 및 반응 처리 수를 줄이는 방법을 제안한다. 실험 결과에 의하면 본 논문의 시스템은 사실적인 영상을 생성할 수 있었고 수초 이내에 가상 인체 모델에 의복을 입힐 수 있었다.

• Journal of Korean Society for Atmospheric Environment
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• 제17권E2호
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• pp.43-51
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• 2001

A report by the national research council in the United States suggested that many lung cancer deaths each year be associated with breathing radon in indoor air. Most of the indoor radon comes directly from soil beneath the basement of foundations. Recently, radon released from groundwater is found to contribute to the total inhalation risk from indoor air. This study presents the quantitative assessment of human exposures to radon released from the groundwater into indoor air. At first, a three-compartment model is developed to describe the transfer and distribution of radon released from groundwater in a house through showering, washing clothes, and flushing toilets. Then, to estimate a daily human exposure through inhalation of such radon for an adult. a physiologically-based pharmacokinetic(PBPK) model is developed. The use of a PBPK model for the inhaled radon could provide useful information regarding the distribution of radon among the organs of the human body. Indoor exposure patterns as input to the PBPK model are a more realistic situation associated with indoor radon pollution generated from a three-compartment model describing volatilization of radon from domestic water into household air. Combining the two models for inhaled radon in indoor air can be used to estimate a quantitative human exposure through the inhalation of indoor radon for adults based on two sets of exposure scenarios. The results obtained from the present study would help increase the quantitative understanding of risk assessment issues associated with the indoor radon released from groundwater.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권11호
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• pp.5436-5458
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• 2017

Automatic Video Surveillance System (AVSS) has become important to computer vision researchers as crime has increased in the twenty-first century. As a new branch of AVSS, baggage detection has a wide area of security applications. Some of them are, detecting baggage in baggage restricted super shop, detecting unclaimed baggage in public space etc. However, in this paper, a detection & classification framework of baggage is proposed. Initially, background subtraction is performed instead of sliding window approach to speed up the system and HSI model is used to deal with different illumination conditions. Then, a model is introduced to overcome shadow effect. Then, occlusion of objects is detected using proposed mirroring algorithm to track individual objects. Extraction of rotational signal descriptor (SP-RSD-HOG) with support plane from Region of Interest (ROI) add rotation invariance nature in HOG. Finally, dynamic human body parameter setting approach enables the system to detect & classify single or multiple pieces of carried baggage even if some portions of human are absent. In baggage detection, a strong classifier is generated by boosting similarity measure based multi layer Support Vector Machine (SVM)s into HOG based SVM. This boosting technique has been used to deal with various texture patterns of baggage. Experimental results have discovered the system satisfactorily accurate and faster comparative to other alternatives.