• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2283-2286
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• 2003

This paper has expressed human's motion data into orthogonal parameters in low dimension, and created new motion data through this. We have reconstructed a new model consisting of orthogonal parameters from dividing human body data into three parts - hand, leg, and body to make new motions. Mixing these parts of body from different motions has leaded to new good motion data. It will be possible to use this motion editing not only for Animation Technology, but also for a three dimensional gesture recognition skill.

• ETRI Journal
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• v.28 no.1
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• pp.107-110
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• 2006

The dimensions of the human body vary by age, sex, and race. The internal structure and outer dimensions of a body exposed to an electromagnetic field is important for accurate dosimetry. The average physical size of Korean adult males between the ages 18 to 24 was investigated, and a male volunteer was selected whose physical condition is within the physical standards, ${\pm}5%$. Magnetic resonance images and partially computerized tomography images of the volunteer were acquired. The intervals between the transverse images were 1 mm for the head and 3 mm for the rest of the body. About 30 different tissues were manually classified by an anatomist on the raw images, and the segmented images were implemented in the form of a text file appropriate for numerical formulation.

• Journal of KIISE:Software and Applications
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• v.36 no.12
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• pp.977-985
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• 2009

This paper proposes a real-time algorithm for tracking the fast moving human body. Although Iterative closest point (ICP) algorithm is suitable for real-time tracking due to its efficiency and low computational complexity, ICP often fails to converge when the human body moves fast because the closest point may be mistakenly selected and trapped in a local minimum. To overcome such limitation, we combine a particle filter based on a motion history information with the ICP. The proposed human body motion tracking algorithm reduces the search space for each limb by employing a hierarchical tree structure, and enables tracking of the fast moving human bodies by using the motion prediction based on the motion history. Experimental results show that the proposed human body motion tracking provides accurate tracking performance and fast convergence rate.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.1
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• pp.108-114
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• 2012

We propose a dispersive finite-difference time domain(FDTD) algorithm suitable for the electromagnetic analysis of the human body. In this work, the dispersion relation of the human body is modeled by a quadratic complex rational function(QCRF), which leads to an accurate and efficient FDTD algorithm. Coefficients(involved in QCRF) for various human tissues are extracted by applying a weighted least square method(WLSM), referred to as the complex-curve fitting technique. We also presents the FDTD formulation for the QCRF-based dispersive model in detail. The QCRFbased dispersive model is significantly accurate and its FDTD implementation is more efficient than the counterpart of the Cole-Cole model. Numerical examples are used to show the validity of the proposed FDTD algorithm.

• Journal of Advanced Navigation Technology
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• v.14 no.3
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• pp.375-383
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• 2010

In this paper, the correlation between voice vowels and human body is analysed for the voice therapy and diagnosis. Using vowels('a', 'e', 'i', 'o', 'u'), the vibration signals in head, chest and belly is measured with the voice signal. As the result, it is shown that body characteristics can be checked from some vowels, and the correlation coefficient of body vibration signal and BMI(body mass index) is computed. From the result, using voice signal and body vibrations, the body diagnosis model is proposed.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.129-132
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• 2002

In this paper, we propose a 3-D animation system to track and analyze motion of the human object. The proposed system consists of two separate layers: motion analysis layer and 3-D model registration layer. Following the MPEG-4 SNHC standard, we generate object motion using body definition and animation parameters. In the implemented system, we acquire human motion data from a single camera and extract body definition parameters from arbitrary VRML human models.

• Journal of Broadcast Engineering
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• v.24 no.2
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• pp.264-272
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• 2019

In this paper, we propose a 3D human body reconstruction and refinement method from the frames extracted from a video to obtain natural and smooth motion in temporal domain. Individual frames extracted from the video are fed into convolutional neural network to estimate the location of the joint and the silhouette of the human body. This is done by projecting the parameter-based 3D deformable model to 2D image and by estimating the value of the optimal parameters. If the reconstruction process for each frame is performed independently, temporal consistency of human pose and shape cannot be guaranteed, yielding an inaccurate result. To alleviate this problem, the proposed method analyzes and interpolates the principal component parameters of the 3D morphable model reconstructed from each individual frame. Experimental result shows that the erroneous frames are corrected and refined by utilizing the relation between the previous and the next frames to obtain the improved 3D human reconstruction result.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.3
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• pp.145-154
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• 2003

Occupant simulation models have been used to study trends or specific design changes in several typical crash situations. The ATB, Articulated Total Body, was developed and used to predict gross human body responses to vehicle crashes and pilot ejections. Since the ATB source code is open to public, the user can add their own defined modules and functions. The introduction of seat belts into cars significantly decreased the injury risk of passengers in frontal impacts. In this paper, a new seat belt model was developed and implemented into the ATB. For this purpose, a subroutine of the new seat belt was constructed. A force-deflection function was added to replace an existing function to consider energy absorption. The function includes hysteresis effects of the experiment data of the loading and unloading parts of the seat belt load-extension curve. Moreover, this belt model considers a slip between ellipsoid and belt segments. This paper attempted to validate the ATB program which includes the subroutine of new belt models comparing with the real car frontal crash experiments and MADYMO frontal models. The analysis focusses on the human movement and body accelerations.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.5
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• pp.494-499
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• 2011

This paper presents the biomechanical analysis and evaluation technology of musculoskeletal system by multi-body human dynamic model and 3-D motion capture data. First, medical image based geometric model and material properties of tissue were used to develop the human dynamic model and 3-D motion capture data based motion analysis techniques were develop to quantify the in-vivo joint kinematics, joint moment, joint force, and muscle force. Walking and push-up motion was investigated using the developed model. The present model and technologies would be useful to apply the biomechanical analysis and evaluation of human activities.

• Journal of the Korea Fashion and Costume Design Association
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• v.25 no.4
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• pp.147-161
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• 2023

This study used 3D anthropometric data from the 8th Size Korea to type and analyze whole body shapes of obese women in their 20s and 30s, and constructed dimensional data for human body items needed to create a 3D human body model for each type. The data analysis used data from 148 obese women in their 20s and 30s, and a total of 48 index values, drop values, and angle items were subjected to factor analysis and one-way variance analysis to categorize body types and verify significant differences by type. As a result of the factor analysis, 12 factors were extracted and divided into 4 body types. Type 1 is a 'standard type with a curved torso with balanced upper and lower body lengths', Type 2 is a 'bending forward type with a short, thick lower body, and an uncurved torso', Type 3 is a 'lean back type with a long and thin lower body and an H-shape torso', Type 4 is a 'sway back type with a long and thick lower body and abdominal obesity'. The representative body type of obese women in their 20s and 30s was identified as Type 1. The constructed body shape information will be used as basic data for future 3D human body modeling.