• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.5
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• pp.201-209
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• 2003

Virtual human models are widely used to save time and expense in vehicle safety studies. A human model is an essential tool to visualize and simulate a vehicle driver in virtual environments. This research is focused on creation and application of a human model fer virtual reality. The Korean anthropometric data published are selected to determine basic human model dimensions. These data are applied to GEBOD, a human body data generation program, which computes the body segment geometry, mass properties, joints locations and mechanical properties. The human model was constituted using MADYMO based on data from GEBOD. Frontal crash and bump passing test were simulated and the driver's motion data calculated were transmitted into the virtual environment. The human model was organized into scene graphs and its motion was visualized by virtual reality techniques including OpenGL Performer. The human model can be controlled by an arm master to test driver's behavior in the virtual environment.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.04a
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• pp.147-151
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• 1999

This paper extends and enhances the existing inverse kinematics technique using the concept of motion characteristic capturing. Motion characteristic capturing is not about measuring motion by tracking body points. Instead, it starts from pre-measured motion data, extracts the motion characteristics, and applies them in animating other bodies. The resulting motion resembles the originally measured one in spite of arbitrary dimensional differences between the bodies. Motion characteristics capturing is a new principle in kinematic motion generalization to process measurements and generate realistic animation of human being or other living creatures.

• The Journal of the Korea Contents Association
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• v.14 no.1
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• pp.24-29
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• 2014

This paper proposes a kinect-based human motion recognition model for the 3D contents control after tracking the human body gesture through the camera in the infrared kinect project. The proposed human motion model in this paper computes the distance variation of the body movement from shoulder to right and left hand, wrist, arm, and elbow. The human motion model is classified into the movement directions such as the left movement, right movement, up, down, enlargement, downsizing. and selection. The proposed kinect-based human motion recognition model is very natural and low cost compared to other contact type gesture recognition technologies and device based gesture technologies with the expensive hardware system.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.3
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• pp.66-71
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• 2006

Some wheelchair users with neuromuscular disorders experience involuntary extensor thrusts, which may cause injuries via impact with the wheelchair, cause the user to slide out of the wheelchair seat, and damage the wheelchair. Knowledge of the human-generated forces during an extensor thrust is of great importance in devising safer, more comfortable wheelchairs. This paper presents an efficient method for identifying human-generated forces during an extensor thrust. We used an inverse dynamic approach with a three-link human body model and a system for measuring human body motion. We developed an experimental system that determines the angular motion of each human body segment and the force at the footrest, which was used to overcome the mathematical indeterminacy of the problem. The proposed method was validated experimentally, illustrating the force-identification process during an extensor thrust.

• International Journal of Human Ecology
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• v.14 no.1
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• pp.41-55
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• 2013

The purpose of this study was to analyze human upper body surface changes at the shoulder and back area. The body surface data were analyzed in terms of muscle and bone displacement in dynamic postures. Body surface data were collected with a 3D body scanner. The body surface was scanned at the static and four baseball batting postures. The body surface dimensions over the deltoids, scapulae and trapezius were measured. The results show that the vertical measurements of the deltoids increased by 20%. The horizontal measurements of the axilla of the back increased. The surface of the trapezius was elongated by over 10%, and the lower back musculature was elongated by about 50%. The results of this study showed that changes in back body surface caused by upper arm movements. It was influenced by the deltoid articulated with the humeri and the scapulae and trapezius. These body surface changes caused by muscle activities and ranges of motion can be used to design functional clothing.

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

• Korean Journal of Human Ecology
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• v.7 no.3
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• pp.15-33
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• 2004

A precise understanding of the human form in static pose serves as the basis of designing clothing. When the human body is in motion, however, even an article of clothing designed to fit the human form in static pose can pull and change, thus restricting the body. In order to increase the fit of the clothing, which may be termed the second skin, its form and measurements therefore must be determined in correlation not only with the formal characteristics of the human body, in static pose but also with its functional characteristics in motion, as caused by the movements of the human body. In this study, the motion factor was selected as the primary basis for designing slacks with good fit in both static and moving states. By indentifying the areas in which lower limb movement cause significant changes in body surface lines, we suggest several application methods for designing slacks. Using unmarried female university students aged 18 - 24 as subjects, a total of 32 body surface categories (15 body surface lines and 17 body surface segment lines) were measured in one static and 9 movement poses. In particular, expansion and contraction levels and rates were measured and used in the analysis. The analysis first involved the calculation of the average measurement per body part in body surface line in static pose as well as of the average expansion and contraction levels and rates in 9 lower limb movements. Two-way MANOVA and multiple comparison analysis (Tukey) were conducted on movements and individual somatotypes regarding measurement per body part and expansion and contraction rates. Body parts whose measurements of body surface lines differed significantly in body surface line in static pose versus in movement were then identified. The results of this study are as follows. First, changes in body surface lines caused by lower limb movements were significant in all body surface lines of the lower trunk, both horizontal and vertical, with the exception of abdomen girth, midway thigh girth, ankle girth, hip length, and posterior knee girth. Second, significantly expanded 10 body surface lines in moving pose were detected and illustrated in table 4. These body parts should be studied in designing or pattern designing, especially for close-fitting pants, in using stretch fabric, and in sensory evaluation of good fit during movement.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.719-722
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• 2009

The purpose of this paper is to develop a robot that moves independently, communicates with a human, and explicitly extracts information from the human mind that is rarely expressed verbally. In a spoken dialog system for information collection, it is desirable to continue communicating with the user as long as possible, but not if the user does not wish to communicate. Therefore, the system should be able to terminate the communication before the user starts to object to using it. In this paper, to enable the construction of a decision model for a system to decide when to stop communicating with a human, we acquired speech and motion data from individuals who were asked many questions by another person. We then analyze their speech and body motion when they do not mind answering the questions, and also when they wish the questioning to cease. From the results, we can identify differences in speech power, length of pauses, speech rate, and body motion.

• The Journal of Korea Robotics Society
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• v.12 no.2
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• pp.239-247
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• 2017

The purpose of this study is to develop a motion generation technique based on a double inverted pendulum model (DIPM) that learns and reproduces humanoid robot (or virtual human) motions while keeping its balance in a pattern similar to a human. DIPM consists of a cart and two inverted pendulums, connected in a serial. Although the structure resembles human upper- and lower-body, the balancing motion in DIPM is different from the motion that human does. To do this, we use the motion capture data to obtain the reference motion to keep the balance in the existence of external force. By an optimization technique minimizing the difference between the motion of DIPM and the reference motion, control parameters of the proposed method were learned in advance. The learned control parameters are re-used for the control signal of DIPM as input of linear quadratic regulator that generates a similar motion pattern as the reference. In order to verify this, we use virtual human experiments were conducted to generate the motion that naturally balanced.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2327-2347
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• 2018

Human actions can be recognized from depth sequences. In the proposed algorithm, we initially construct depth, motion maps (DMM) by projecting each depth frame onto three orthogonal Cartesian planes and add the motion energy for each view. The body part of the action (BPoA) is calculated by using bounding box with an optimal window size based on maximum spatial and temporal changes for each DMM. Furthermore, feature vector is constructed by using BPoA for each human action view. In this paper, we employed an ensemble based learning approach called Rotation Forest to recognize different actions Experimental results show that proposed method has significantly outperforms the state-of-the-art methods on Microsoft Research (MSR) Action 3D and MSR DailyActivity3D dataset.