• Journal of Internet Computing and Services
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• v.7 no.1
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• pp.65-74
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• 2006

Human tracking is a requirement for the advanced human-computer interface (HCI), This paper proposes a method which uses a component-based human model, detects body parts, estimates human postures, and animates an avatar, Each body part consists of color, connection, and location information and it matches to a corresponding component of the human model. For human tracking, the 2D information of human posture is used for body tracking by computing similarities between frames, The depth information is decided by a relative location between components and is transferred to a moving direction to build a 2-1/2D human model. While each body part is modelled by posture and directions, the corresponding component of a 3D avatar is rotated in 3D using the information transferred from the human model. We achieved 90% tracking rate of a test video containing a variety of postures and the rate increased as the proposed system processed more frames.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.3
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• pp.193-200
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• 2012

A numerical analysis is carried out in order to obtain aerodynamic data of the ski jump. The body modelling of Korean people is used in the numerical simulation and the result is validated by comparing it with the wind tunnel experiment. A flying posture, which provides the maximum lift-to-drag ratio, is found by analyzing the aerodynamic coefficients of various flight conditions. The result of the present study can be applied to fixing the postures of Korean ski players and is expected to advance the national sports science.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.6
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• pp.48-54
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• 2007

This paper describes the analysis of transient phenomena on the point that a human body suffers an electrical shock. A couple of case studies were discussed by using an ATPDraw simulation tool. Two models for the case studies were constructed on the assumption that the electrical shock event takes place under water to simulate the severest condition ; the first model that the human body contacts with an energized part exposed to water ; the second model that both hands and feet simultaneously contact with the ground under water. After modeling, the transient phenomena for the models were analyzed by comparing the voltages and currents calculated at each part of the human body. As a result steep front kicks in voltage and current were observed as transient phenomena on the point that the human body contacts with the energized part exposed to water in the first model and the magnitudes of the kicks considerably increased. It was considered however, the effect of the kicks due to the commercial power source on the human body could be neglected because the product of the current through the body and the short duration is less than the safety limit. When both hands and feet simultaneously contact with the ground in the second model, the voltage generally decreased all over the body parts, while the current flowing through the chest abruptly increased. The duration of this current was very shot, as well, thus its effect on the electrical shock is considered insignificant. After all, it was confirmed through the simulation results that the electrical shock depends on the magnitude in voltage and the body impedance.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2003.09a
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• pp.77-77
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• 2003

CT와 MRI의 단면 영상을 대상으로 영상분할 (Image segmentation)과 Image registration방법을 이용하여 인체 모델을 개발 하고자 한다. 우선 인체의 Head와 Neck부분의 CT와 MR 영상을 얻어 뼈, 근육, 인대, 그리고 그 밖의 장기의 해부학적 영상 특징을 분석하였다. 인체의 Head와 Neck 부분에 대한 CT와 MR 영상에 대해 각 부위별로 ROI(region-of-interrest)를 설정하였고, 각 volxel 마다 3차원 좌표를 계산할 수 있는 소프트웨어를 개발하였다. 특히 각 해부학적 영상에서 부위별로 CT 번호를 분석하고, pulse sequence에 따른 MRI 영상의 부위별 특정을 분석하였다. 이 분석한 자료를 바탕으로 영상 분할을 하였다. 영상 분할전에 각종 잡음(noise) 제거 및 영상 분할을 효과적으로 처리하기 위해 기본적인 영상처리 (filtering)를 구현하였고, 대조도(contrast) 및 밝기(brightness)를 조절할 수 있게 프로그램을 구현하였다. 영상 분할 방법 중 선(line) 및 에지(edge) 의 검출 방법, 문턱치화(threshold) 방법, 영역확대(region growing) 방법으로 영상 분할을 해봄으로써 우리의 인체 모델링 개발에 가장 적합한 영상 분할 알고리듬 방법을 찾도록 시도하였다. 결과적으로 말하면, 한가지 방법의 알고리듬을 쓰는 것보다는 인체의 부위에 따라 두 가지 이상의 알고리듬 방법을 쓰는 것이 원하고자 하는 부위를 영상 분할하는데 더 효과적이다는 것을 알게 되었다. 우리의 연구 과제에서는 영역확대(region growing) 방법과 문턱치화 방법, 모드법(피크니스, 밸리)의 알고리듬을 이용하여 영상 분할을 한 결과 우리가 얻고자 하는 인체 부위별 중 근육과 뼈를 구별하는데는 별 무리가 없었으나, 인대 및 기타 장기를 구별하는데는 어려움을 겪게 되었다. 이후에 좀더 알고리듬을 연구하여 이번 연구에서 구별하기 어려운 장기 부분도 구별 할 수 있도록 노력하겠다.

• CDE review
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• v.13 no.1
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• pp.28-35
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• 2007

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.995-996
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• 2010

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.7
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• pp.785-790
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• 2011

The goal of this study is to estimate the force acting on the knee joint in the human body by using the Hilltype muscle model based on a musculoskeletal model of the human lower extremity in the sagittal plane. For estimating the force applied, the human leg is modeled using multi-body modeling. This leg model comprises biarticular muscles acting on two joints of the upper and lower limbs, and the muscles include some of the major muscles such as the hamstring. In order to analyze the uncertainty of the applied forces acting on the knee joint, statistical distributions of human body, leg part, parameters are required and to obtain the parameter's statistical characteristic of the part sample survey method is employed. Finally, by using the sensitivity information of the parameters, the force acting on the knee joint can be estimated.

• Journal of IKEEE
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• v.24 no.1
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• pp.120-126
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• 2020

We present a user recognition method using human body impulse response signals. The body compositions vary from person to person depending on the portion of water, muscle, and fat. In the body communication study, the body has been interpreted circuit models using capacitance and resistances, and its characteristics are determined by the body compositions. Therefore, the individual body channel is unique and can be used for user recognition. In this paper, we applied pseudo impulse signals to the left hand and recorded received signals from the right hand. The empirical mode decomposition (EMD) method removed noise from the received signals and 10 peak values are extracted. We set the differences between peak amplitudes as a key feature to identify individuals. We collected data from 6 subjects and achieved accuracy of 97.71% for the user recognition application.

• Electronics and Telecommunications Trends
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• v.27 no.3
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• pp.12-21
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• 2012

최근 3DTV, 입체 모니터, 입체 노트북 등이 출시되고, 3D 영화, 게임 등 3D 관련 산업이 성장하면서 관련 콘텐츠의 요구사항이 증가하고 있다. 특히, 3D 콘텐츠의 주요 요소 중 하나인 인체는 전통적으로 고가의 3D 스캐너를 이용해 모델링하는 방식을 주로 사용해 왔다. 하지만 근래에는 광학 기술 및 컴퓨팅 성능의 향상으로 구조광과 같은 능동 센서나 카메라로부터 획득한 영상을 기반으로 3D 인체 외형을 복원하는 연구가 각광을 받고 있다. 이런 추세에 발맞춰 본고에서는 인체 중에서도 사용자의 민감도가 높은 얼굴의 3D 복원 기술 및 연구 동향을 살펴보고, 다양한 응용을 목적으로 ETRI에서 개발 중인 3D 얼굴 복원 기술을 소개하고자 한다.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.186-192
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• 2009

In this paper, we represent the recognition method for human frontal upper body pose. In HCI(Human Computer Interaction) and HRI(Human Robot Interaction) when a interaction is established the human has usually frontal direction to the robot or computer and use hand gestures then we decide to focus on human frontal upper-body pose, The two main difficulties are firstly human pose is consist of many parts which cause high DOF(Degree Of Freedom) then the modeling of human pose is difficult. Secondly the matching between image features and modeling information is difficult. Then using Pictorial Model we model the human main poses which are mainly took the space of frontal upper-body poses and we recognize the main poses by making main pose database. using determined main pose we used the model parameters for particle filter which predicts the posterior distribution for pose parameters and can determine more specific pose by updating model parameters from the particle having the maximum likelihood. Therefore based on recognizing main poses and tracking the specific pose we recognize the human frontal upper body poses.