• Journal of the Korea Fashion and Costume Design Association
• /
• v.22 no.1
• /
• pp.1-13
• /
• 2020

The purpose of this study is to create a 3D avatar from 3D human body shape data using the CLO 3D virtual clothing program and to verify the feasibility of avatar production using the virtual clothing system for verifying size and shape. The research method was to select one virtual representative model that is the closest to the mean size of each body item for each age group. Using the 3D human body scan shape of a 40-69 years old male was applied to the CLO 3D virtual wearing system. Using the CLO 3D Avatar conversion menu, we verified the feasibility of creating a 3D avatar that reproduces the human body scan shape. In the dimension comparison between the 3D avatar and the fictitious representative model, the dimension difference was noticeable in height, circumference, and length. However, as a result, the converted 3D avatar showed less than a 5% difference in most human dimensions. In addition, since the body shape and posture were reproduced similarly, the utilization of the avatar was verified.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.4
• /
• pp.851-859
• /
• 2011

In this paper, we propose the method that automatically extracts the silhouette and the joints of consecutive input image, and track joints to trace object for interaction between human and computer. Also the proposed method presents the action of human being to map human body using joints. To implement the algorithm, we model human body using 14 joints to refer to body size. The proposed method converts RGB color image acquired through a single camera to hue, saturation, value images and extracts body's silhouette using the difference between the background and input. Then we automatically extracts joints using the corner points of the extracted silhouette and the data of body's model. The motion of object is tracted by applying block-matching method to areas around joints among all image and the human's motion is mapped using positions of joints. The proposed method is applied to the test videos and the result shows that the proposed method automatically extracts joints and effectively maps human body by the detected joints. Also the human's action is aptly expressed to reflect locations of the joints

• ETRI Journal
• /
• v.37 no.3
• /
• pp.439-449
• /
• 2015

Human body communication (HBC) is being recognized as a new communication technology for mobile and wearable devices in a body area network (BAN). This paper presents co-channel interference experienced by HBC supporting the physical layer in the IEEE 802.15.6 BAN standard. To analyze the co-channel interference, a co-channel interference model is introduced, and space-domain and time-domain parameters representing an interference environment are generated using the co-channel interference model. A new signal-to-interference ratio (SIR) parameter depending on the peak amplitudes of the data signals causing co-channel interference is defined; co-channel interference can be easily analyzed and modelled using the newly defined SIR. The BER degradation model derived using the co-channel interference model and SIR in this paper can be effectively used to estimate the performance.

• The Journal of Korean Institute of Next Generation Computing
• /
• v.15 no.4
• /
• pp.40-50
• /
• 2019

In recent years, it is important to visualize an accurate human body model for the low-end system in the medical imaging field where augmented reality technology and virtual reality technology are used. Decreasing the geometry of a model causes a difference from the original shape and considers the difference as an error. So, the error should be minimized while reducing geometry. In this study, the organ areas of a human body in the tomographic images such as CT or MRI is segmented and 3D geometric model is generated, thereby implementing the reconstruction method of multiple resolution level-of-detail model. In the experiment, a virtual reality platform was constructed to verify the shape of the reconstructed model, targeting the spine area. The 3D human body model and patient information can be verified using the virtual reality platform.

• Journal of the Ergonomics Society of Korea
• /
• v.22 no.1
• /
• pp.1-15
• /
• 2003

The resonance behaviour needs be understood to identify the mechanisms responsible for the dynamic characteristics of human body, to allow for the non-linearity when predicting the influence of seating dynamics, and to predict the adverse effects caused by various magnitudes of vibration. However, there are currently no known studies on the effect of vibration magnitude on the transmissibility to thoracic or lumbar spine of the seated person, despite low back pain(LBP) being the most common ailment associated with whole-body vibration. The objective of this paper is to develop a proper mathematical human model for LBP and musculoskeletal injury of the crew in a maritime vehicle. In this study, 7 degree-of-freedom including 2 non-rigid mass representing wobbling visceral and intestine mass, is proposed. Also, when compared with previously published experimental results, the model response was found to be well-matching. When exposed to various of vertical vibration, the human model shows appreciable non-linearity in its biodynamic responses. The relationships of resonance for LBP and musculoskeletal injury during whole-body vibration are also explained.

• Journal of KIISE:Software and Applications
• /
• v.36 no.12
• /
• pp.996-1008
• /
• 2009

This paper proposes a novel approach for the model-based pose matching of a human body using Active Shape Models. To improve the processing time of model creation and registration, we use a skeleton-type model instead of the conventional silhouette-based models. The skeleton model defines feature information that is used to match the human pose. Images used to make the model are for 600 human bodies, and the model has 17 landmarks which indicate the body junction and key features of a human pose. When applying primary Active Shape Models to the skeleton-type model in the matching process, a problem may occur in the proximal joints of the arm and leg due to the color variations on a human body and the insufficient information for the fore-rear directions of profile normals. This problem is solved by using the background subtraction information of a body region in the input image and adding a 4-directions feature of the profile normal in the proximal parts of the arm and leg. In the matching process, the maximum iteration is less than 30 times. As a result, the execution time is quite fast, and was observed to be less than 0.03 sec in an experiment.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.10b
• /
• pp.509-514
• /
• 2006

Human action recognition is an active research area in computer vision. In this paper, we present a robust method for human action recognition by using combined information of human body shape and motion information with multiple views image sequence. The principal component analysis is used to extract the shape feature of human body and multiple block motion of the human body is used to extract the motion features of human. This combined information with multiple view sequences enhances the recognition of human action. We represent each action using a set of hidden Markov model and we model each action by multiple views. This characterizes the human action recognition from arbitrary view information. Several daily actions of elderly persons are modeled and tested by using this approach and they are correctly classified, which indicate the robustness of our method.

• Journal of the Korean Society for Precision Engineering
• /
• v.24 no.11
• /
• pp.116-125
• /
• 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 Korea Computer Graphics Society
• /
• v.3 no.1
• /
• pp.1-7
• /
• 1997

Technology for the realistic model and the motion control of human is applied to many areas of computer graphics, virtual reality and computer simulations. Human body is a multi-articular body. Generally, to create a human model and motions. articulated body models are generated and their motions are controlled based upon kinematics. The hand of the human consists of many small articulations and each articulations have a various degree of freedom. This paper presents a model of human hand which is based on the two kinds of constraints to control the motions of the hand realistically. To build a hand model, we experimented the anatomy of the human hand, and the diverse motions of the hand are tested.

• The Journal of Korea Robotics Society
• /
• v.3 no.4
• /
• pp.287-299
• /
• 2008

People have expected a humanoid robot to move as naturally as a human being does. The natural movements of humanoid robot may provide people with safer physical services and communicate with persons through motions more correctly. This work presented a methodology to generate the natural motions for a humanoid robot, which are converted from human motion capture data. The methodology produces not only kinematically mapped motions but dynamically mapped ones. The kinematical mapping reflects the human-likeness in the converted motions, while the dynamical mapping could ensure the movement stability of whole body motions of a humanoid robot. The methodology consists of three processes: (a) Human modeling, (b) Kinematic mapping and (c) Dynamic mapping. The human modeling based on optimization gives the ZMP (Zero Moment Point) and COM (Center of Mass) time trajectories of an actor. Those trajectories are modified for a humanoid robot through the kinematic mapping. In addition to modifying the ZMP and COM trajectories, the lower body (pelvis and legs) motion of the actor is then scaled kinematically and converted to the motion available to the humanoid robot considering dynamical aspects. The KIST humanoid robot, Mahru, imitated a dancing motion to evaluate the methodology, showing the good agreement in the motion.