• 제목/요약/키워드: Human Body Model

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타원체 모델과 깊이값 포인트 매칭 기법을 활용한 사람 움직임 추적 기술 (Human Motion Tracking based on 3D Depth Point Matching with Superellipsoid Body Model)

  • 김남규
    • 디지털콘텐츠학회 논문지
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    • 제13권2호
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    • pp.255-262
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    • 2012
  • 사람 움직임 추적 알고리즘은 인간과 컴퓨터 상호작용, 화상회의, 감시 시스템, 게임 및 엔터테인먼트 분야에서 반드시 필요한 기술로 인식되고 있다. 과거 다양한 사람 움직임 추적 알고리즘들이 응용 프로그램의 특성에 따라 구현되고, 실시간성을 고려한 보다 효율적인 영상 처리, 컴퓨터 비전, 인터페이스 기술들을 적용하여 구현되고 있다. 본 논문에서는 타원체 형태의 신체 모델과 깊이값 정보를 갖는 3차원 점들과의 매칭을 통해 실시간으로 적용 가능한 움직임 추적 기술을 소개한다. 움직임 추적을 위한 기반 모델은 사람의 모습과 유사한 형태의 타원체 조합의 18개의 관절을 갖는 형태로 구성되어 지며, 영상으로부터 들어온 사람의 모습을 분석하여 일련의 신체 부위를 나누고, 그 정보를 바탕으로 역기구학 기반의 초기 자세를 추출한다. 초기 자세는 3차원 점 매칭 기법을 활용하여 보다 정확한 자세로 수정된다.

Human Activity Recognition Using Spatiotemporal 3-D Body Joint Features with Hidden Markov Models

  • Uddin, Md. Zia;Kim, Jaehyoun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권6호
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    • pp.2767-2780
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    • 2016
  • Video-based human-activity recognition has become increasingly popular due to the prominent corresponding applications in a variety of fields such as computer vision, image processing, smart-home healthcare, and human-computer interactions. The essential goals of a video-based activity-recognition system include the provision of behavior-based information to enable functionality that proactively assists a person with his/her tasks. The target of this work is the development of a novel approach for human-activity recognition, whereby human-body-joint features that are extracted from depth videos are used. From silhouette images taken at every depth, the direction and magnitude features are first obtained from each connected body-joint pair so that they can be augmented later with motion direction, as well as with the magnitude features of each joint in the next frame. A generalized discriminant analysis (GDA) is applied to make the spatiotemporal features more robust, followed by the feeding of the time-sequence features into a Hidden Markov Model (HMM) for the training of each activity. Lastly, all of the trained-activity HMMs are used for depth-video activity recognition.

Human body model electrostatic discharge tester using metal oxide semiconductor-controlled thyristors

  • Dong Yun Jung;Kun Sik Park;Sang In Kim;Sungkyu Kwon;Doo Hyung Cho;Hyun Gyu Jang;Jongil Won;Jong-Won Lim
    • ETRI Journal
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    • 제45권3호
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    • pp.543-550
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    • 2023
  • Electrostatic discharge (ESD) testing for human body model tests is an essential part of the reliability evaluation of electronic/electrical devices and components. However, global environmental concerns have called for the need to replace the mercury-wetted relay switches, which have been used in ESD testers. Therefore, herein, we propose an ESD tester using metal oxide semiconductor-controlled thyristor (MCT) devices with a significantly higher rising rate of anode current (di/dt) characteristics. These MCTs, which have a breakdown voltage beyond 3000 V, were developed through an in-house foundry. As a replacement for the existing mercury relays, the proposed ESD tester with the developed MCT satisfies all the requirements stipulated in the JS-001 standard for conditions at or below 2000 V. Moreover, unlike traditional relays, the proposed ESD tester does not generate resonance; therefore, no additional circuitry is required for resonant removal. To the best of our knowledge, the proposed ESD tester is the first study to meet the JS-001 specification by applying a new switch instead of an existing mercury-wetted relay.

태권도 옆차기 동작의 동력학해석과 충격해석에 관한 연구 (A Study on the Dynamic and Impact Analysis of Side Kick in Taekwondo)

  • 이중현;한규현;이현승;이은엽;이영신
    • 대한기계학회논문집A
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    • 제32권1호
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    • pp.83-90
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    • 2008
  • Taekwondo is a martial art form and sport that uses the hands and foot for attack and defense. Taekwondo basic motion is composed of the breaking, competition and poomsea motion. In the side kick among the competition motion, the impact force is larger than other kinds of kicks. The side kick with the front foot can be made in two steps. In the first step, the front foot is stretched forward from back stance free-fighting position. For the second step, the rear foot is followed simultaneously. Then, the kick is executed while entire body weight rests on the rear foot. In this paper, impact analysis of the human model for hitting posture is carried out. The ADAMS/LifeMOD is used in hitting modeling and simulation. The simulation model creates the human model to hit the opponent. As the results, the dynamic analysis of human muscle were presented.

Dynamic gesture recognition using a model-based temporal self-similarity and its application to taebo gesture recognition

  • Lee, Kyoung-Mi;Won, Hey-Min
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제7권11호
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    • pp.2824-2838
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    • 2013
  • There has been a lot of attention paid recently to analyze dynamic human gestures that vary over time. Most attention to dynamic gestures concerns with spatio-temporal features, as compared to analyzing each frame of gestures separately. For accurate dynamic gesture recognition, motion feature extraction algorithms need to find representative features that uniquely identify time-varying gestures. This paper proposes a new feature-extraction algorithm using temporal self-similarity based on a hierarchical human model. Because a conventional temporal self-similarity method computes a whole movement among the continuous frames, the conventional temporal self-similarity method cannot recognize different gestures with the same amount of movement. The proposed model-based temporal self-similarity method groups body parts of a hierarchical model into several sets and calculates movements for each set. While recognition results can depend on how the sets are made, the best way to find optimal sets is to separate frequently used body parts from less-used body parts. Then, we apply a multiclass support vector machine whose optimization algorithm is based on structural support vector machines. In this paper, the effectiveness of the proposed feature extraction algorithm is demonstrated in an application for taebo gesture recognition. We show that the model-based temporal self-similarity method can overcome the shortcomings of the conventional temporal self-similarity method and the recognition results of the model-based method are superior to that of the conventional method.

K-means와 CNN을 활용한 체지방율 분석 모델 설계 및 구현 (Design and Implentation of Body Fat Percentage Analysis Model using K-means and CNN)

  • 이태준;박찬명;김창수;정회경
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2021년도 추계학술대회
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    • pp.329-331
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    • 2021
  • 최근 헬스케어 분야에서 딥러닝을 활용한 다양한 사례가 증가하면서 웨어러블 기기를 통한 심전도 검사, 체성분 분석 등의 기능을 제공하여 합리적인 의사 결정을 제공하여 개인에게 맞는 프로세스를 제공할 수 있다. 딥러닝을 활용하기 위해서는 정제된 데이터 확보가 무엇보다 중요하며 이러한 데이터는 사람의 개입이나 비지도학습 등을 통해 이뤄지고 있다. 본 논문에서는 측정하기 쉬운 가슴둘레, 허리둘레와 같은 치수 데이터를 이용해 성별과 나이에 따른 군집별 비지도학습을 진행하고 이를 CNN으로 분류하는 모델을 제안한다. 데이터는 국가기술표준원에서 제공하고 있는 제7차 인체치수데이터를 활용하였다. 이를 통해 개인 맞춤형 체형관리 서비스나 비만 분석 등 다양한 응용 사례에 적용할 수 있을 것으로 사료된다.

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한국인 인체 모델의 개발과 적용 (Development and Application of Korean Dummy Models)

  • 이상철;손권;김성진
    • 대한인간공학회지
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    • 제21권2호
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    • pp.13-23
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    • 2002
  • Human dummies are essential tools in the development of such products as vehicle have been actively used not only in reach and view field tests. but also in impact perception evaluations. This study attempted to obtain geometric and dynamic model body segments from Korean anthropometric data. The investigation focused on the de both human and dummy for the geometric and inertial properties. The dynamic modeli being suggested is based on rigid body dynamics using fifteen individual body segments by joins. The segments are connected at the locations representing the physical joint body so that each segment has its mass and moment of inertia. For visual three-dimensional graphic was used for easier implementation of the dumn applications. For applications, proposed Korean dummies Were used in dynamic crash and driver's view and reach test modules were developed in virtual environment.

보행 중 인체 슬관절의 3차원 접촉 모델 개발 (Development of Three-Dimensional Contact Model of Human Knee Joint During Locomotion)

  • 김효신;박성진;문정환
    • 한국정밀공학회지
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    • 제22권11호
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    • pp.182-189
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    • 2005
  • The human knee joint is the intermediate joint of the lower limb that is the largest and most complex joint in the body. Understanding of joint-articulating surface motion is essential for the joint wear, stability, mobility, degeneration, determination of proper diagnosis and so on. However, many studies analyzed the passive motion of the lower limb because of the skin marker artefact and some studies described medial and lateral condyle of a femur as a simple sphere due to the complexity of geometry. Thus, in this paper, we constructed a three-dimensional geometric model of the human knee from the geometry of its anatomical structures using non-uniform B-spline surface fitting as a study for the kinematic analysis of more realistic human knee model. In addition, we developed and verified 6-DOF contact model of the human knee joint using $C^2$ continuous surface of the inferior region of a femur, considering the relative motion of shank to thigh during locomotion.

급속조형기술을 이용한 인체모형의 제작에 관한 연구

  • 이태영;김항묵;채수원;장준근
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1995년도 추계학술대회 논문집
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    • pp.903-906
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    • 1995
  • In this paper,human body models have been manufactured by the use of rapid prototyping techniques, which are to be used for surgery planning in clinical practice. In this manufactacturing process, CT or MRI data of human bodies are prepared and the images are processed to obtain sectional contours. With these contours, three-dimensional surface triangulated models are constructed, which finally transformed to STL file for rapid prototyping. For this purpose, total service system for manufacturing of human body models is constructed by employing commercial softwares, and the related problems and process parameters are investigated

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Motion Capture of the Human Body Using Multiple Depth Sensors

  • Kim, Yejin;Baek, Seongmin;Bae, Byung-Chull
    • ETRI Journal
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    • 제39권2호
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    • pp.181-190
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    • 2017
  • The movements of the human body are difficult to capture owing to the complexity of the three-dimensional skeleton model and occlusion problems. In this paper, we propose a motion capture system that tracks dynamic human motions in real time. Without using external markers, the proposed system adopts multiple depth sensors (Microsoft Kinect) to overcome the occlusion and body rotation problems. To combine the joint data retrieved from the multiple sensors, our calibration process samples a point cloud from depth images and unifies the coordinate systems in point clouds into a single coordinate system via the iterative closest point method. Using noisy skeletal data from sensors, a posture reconstruction method is introduced to estimate the optimal joint positions for consistent motion generation. Based on the high tracking accuracy of the proposed system, we demonstrate that our system is applicable to various motion-based training programs in dance and Taekwondo.