• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.1
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• pp.96-104
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• 2009

An anatomically detailed elderly human body model is under development. Using the anthropometric database of domestic nation-wide size survey, SizeKorea, a standard size and shape of 50th %tile elderly was constructed. Through the local recruitment process, a male volunteer with 71 years of age, 163cm of height and 63kg of weight has been selected. The exterior (skin) and interior (skeleton and organ) geometries were acquired from whole body 3D laser scan and various medical images such as CT, X-ray, and Ultrasonic of the volunteer. A particular attention has been paid into the combining process of exterior and interior geometries especially for joint articulation positions since they were measured at different postures (sitting vs. supine). A whole ribcage of PMHS which possessed similar anthropometry and age of standard 50th %tile elderly was prepared and dissected for the precise gauge of cortical rib bone thickness distributions. After completing the morphological construction of elderly human body, the finite element modeling will be processed by meshing elements and assigning mechanical properties to various biological tissues which reflect the aging effect.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2839-2852
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• 2013

Context-awareness is an essential part of ubiquitous computing, and over the past decade video based activity recognition (VAR) has emerged as an important component to identify user's context for automatic service delivery in context-aware applications. The accuracy of VAR significantly depends on the performance of the employed human body segmentation algorithm. Previous human body segmentation algorithms often engage modeling of the human body that normally requires bulky amount of training data and cannot competently handle changes over time. Recently, active contours have emerged as a successful segmentation technique in still images. In this paper, an active contour model with the integration of Chan Vese (CV) energy and Bhattacharya distance functions are adapted for automatic human body segmentation using depth cameras for VAR. The proposed technique not only outperforms existing segmentation methods in normal scenarios but it is also more robust to noise. Moreover, it is unsupervised, i.e., no prior human body model is needed. The performance of the proposed segmentation technique is compared against conventional CV Active Contour (AC) model using a depth-camera and obtained much better performance over it.

• International conference on construction engineering and project management
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• 2022.06a
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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.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.11
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• pp.116-125
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• 2007

Human muscle skeletal model was developed for biomechanical study. The human model was consists with 19 bone-skeleton and 122 muscles. Muscle number of upper limb, trunk and lower limb part are 28, 60, 34 respectively. Bone was modeled with 3D beam element and muscle was modeled with spar element. For upper limb muscle modelling, rectus abdominis, trapezius, deltoideus, biceps brachii, triceps brachii muscle and other main muscles were considered. Lower limb muscle was modeled with gastrocenemius, gluteus maximus, gluteus medius and related muscles. The biomechanical stress and strain analysis of human was conducted by proposed finite element analysis model under Kumdo head hitting motion. In this study structural analysis has been performed in order to investigate the human body impact by Kumdo head hitting motion. As the results, the analytical displacement, stress and strain of human body are presented.

• 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.

• Korean Journal of Human Ecology
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• v.23 no.6
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• pp.1171-1189
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• 2014

In order to provide the basic data for creating the environment which can efficiently reflect prefer fit along with body size when selecting clothes size in the indirect purchasing environment, this study analyzed the difference of ready-made jacket part-specific fit preferred by fashion models in their twenties and female college students. This study was to analyze the impact of body size, recognition of body part-specific characteristics shape, body satisfaction on prefer fit of jacket. As for the difference of prefer fit depending on the body size, female college students preferred more loose fit than models. The difference according to recognition of body part-specific characteristics shape turned out to be significant for prefer fit depending on the degree of bend of neck, arm length, bend of back recognition and matching fit was found to be preferred as they recognize their body shape to be normal and the difference according to body satisfaction appeared to be significant in the terms of bend of back, hip width/protrusion, torso size/length, sleeve length, whole body shape and they turned out to prefer matching fit as they are satisfied with their body. As shown above, body size, recognition of body part-specific characteristics shape, especially body satisfaction have a great influence on prefer fit of jacket and therefore, if preparing for a size selection step according to body shape and satisfaction in the jacket size selection process, customers' satisfaction in jacket size may be improved and it is considered to be helpful for both consumers and sellers.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.752-757
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• 1991

Recently, human body modeling with muscle deformation has become an attractive research area in computer animation. There are many modeling tools available for solids such as mechanical part. However, there are many limitations of these conventional methods in modeling flexible objects with delicate motions and shapes such as human bodies. In this paper we present a new modeling technique for human body with muscle deformation. Each muscle is represented as a generalized cylinder and its shape deformation is computed using simple algorithm. The human body is a union of muscles, bones, organs, etc. The modeling data are obtained from the information on the human anatomy. To demonstrate the feasibility of our method, we model several arm muscles and simulate the skin deformation. As a result we have obtained a realistic shape deformation.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.619-628
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• 2011

Normally vision-based 3D human pose recognition technology is used to method for convey human gesture in HCI(Human-Computer Interaction). 2D pose model based recognition method recognizes simple 2D human pose in particular environment. On the other hand, 3D pose model which describes 3D human body skeletal structure can recognize more complex 3D pose than 2D pose model in because it can use joint angle and shape information of body part. In this paper, we describe a development of interactive game contents using pose recognition interface that using 3D human body joint information. Our system was proposed for the purpose that users can control the game contents with body motion without any additional equipment. Poses are recognized comparing current input pose and predefined pose template which is consist of 14 human body joint 3D information. We implement the game contents with the our pose recognition system and make sure about the efficiency of our proposed system. In the future, we will improve the system that can be recognized poses in various environments robustly.