• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.5
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• pp.434-441
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• 2004

In this paper, an exoskeleton-type motion capturing system is designed and implemented. The device is designed to have 12 degree-of-freedom entirely to represent human arm motions. Forward and inverse kinematics of the device are analyzed to make sure of its singular positions. With the designed model parameters, simulation studies are conducted to verify that the designed motion capturing system is effective to represent human motions within the workspace. As a counterpart of the exoskeleton system, a mobile robot is built to follow human motion restrictively. Experimental studies of teleoperation from the exoskeleton device to control the mobile robot are carried out to show feasible application of wireless man-machine interface.

• Journal of Fashion Business
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• v.19 no.3
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• pp.130-143
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• 2015

By studying 3-D virtual human modeling, motion-capturing and clothing simulation for easier and safer work clothes development, this research aimed (1) to categorize heavy manufacturing work motions; (2) to generate a 3-D virtual male model and establish painting work motions within a 3-D virtual clothing simulation system through computerized body scanning and motion-capturing; and finally (3) to suggest simulated clothing images of painting work clothes developed based on virtual male avatar body measurements by implementing the work motions defined in the 3-D virtual clothing simulation system. For this, a male subject's body was 3-D scanned and also directly measured. The procedures to edit a 3-D virtual model required the total body shape to be 3-D scanned into a digital format, which was revised using 3-D Studio MAX and Maya rendering tools. In addition, heavy industry workers' work motions were observed and recorded by video camera at manufacturing sites and analyzed to categorize the painting work motions. This analysis resulted in 4 categories of motions: standing, bending, kneeling and walking. Besides, each work motion category was divided into more detailed motions according to sub-work posture factors: arm angle, arm direction, elbow bending angle, waist bending angle, waist bending direction and knee bending angle. Finally, the implementation of the painting work motions within the 3-D clothing simulation system presented the virtual painting work clothes images simulated in a dynamic mode.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.321-323
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• 2015

Monitoring crane motion in real time is the first step to identifying and mitigating crane-related hazards on construction sites. However, no accurate and reliable crane motion capturing technique is available to serve this purpose. The objective of this research is to explore a method for real-time crane motion capturing and investigate an approach for assisting hazard detection. To achieve this goal, this research employed various techniques including: 1) a sensor-based method that accurately, reliably, and comprehensively captures crane motions in real-time; 2) computationally efficient algorithms for fusing and processing sensing data (e.g., distance, angle, acceleration) from different types of sensors; 3) an approach that integrates crane motion data with known as-is environment data to detect hazards associated with lifting tasks; and 4) a strategy that effectively presents crane operator with crane motion information and warn them with potential hazards. A prototype system was developed and tested on a real crane in a field environment. The results show that the system is able to continuously and accurately monitor crane motion in real-time.

• The Journal of Korea Robotics Society
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• v.2 no.2
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• pp.143-151
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• 2007

This paper deals with a tangible interface system that introduces robot as remote avatar. It is focused on a new method which makes a robot imitate human arm motions captured from a remote space. Our method is functionally divided into two parts: capturing human motion and adapting it to robot. In the capturing part, we especially propose a modified potential function of metaballs for the real-time performance and high accuracy. In the adapting part, we suggest a geometric scaling method for solving the structural difference between a human and a robot. With our method, we have implemented a tangible interface and showed its speed and accuracy test.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2011.05a
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• pp.67-68
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• 2011

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.2
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• pp.145-153
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• 2006

An optimal capturing trajectory for a moving object is proposed in this paper based on the observation that a single-curvature path is more accurate than double-or triple-curvature paths. Moving distance, moving time, and trajectory error are major factors considered in deciding an optimal path for capturing the moving object. That is, the moving time and distance are minimized while the trajectory error is maintained as small as possible. The three major factors are compared for the single and the double curvature trajectories to show superiority of the single curvature trajectory. Based upon the single curvature trajectory, a kinematics model of a mobile robot is proposed to follow and capture the moving object, in this paper. A capturing scenario can be summarized as follows: 1. Motion of the moving object has been captured by a CCD camera., 2. Position of the moving object has been estimated using the image frames, and 3. The mobile robot tries to follow the moving object along the single curvature trajectory which matches positions and orientations of the moving object and the mobile robot at the final moment. Effectiveness of the single curvature trajectory modeling and capturing algorithm has been proved, through simulations and real experiments using a 2-DOF wheel-based mobile robot.

• Korean Journal of Applied Biomechanics
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• v.25 no.1
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• pp.123-130
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• 2015

Purpose : The purpose of this study was to investigate the reliability of 3D-inertia measurement unit (IMU) based shoes in gait analysis. This was done with respect to the results of the optical motion capturing system and to collect reference gait data of healthy subjects with this device. Methods : The Smart Balance$^{(R)}$ system of 3D-IMU based shoes and Osprey$^{(R)}$ motion capturing cameras were used to collect motion data simultaneously. Forty four healthy subjects consisting of individuals in 20s (N=20), 40s (N=13), and 60s (N=11) participated in this study voluntarily. They performed natural walking on a treadmill for one minute at 4 different target speeds (3, 4, 5, 6 km/h), respectively. Results : Cadence (ICC=.998), step length (ICC=.970), stance phase (ICC=.845), and double-support phase (ICC=.684) from 3D-IMU based shoes were in agreement with results of optical motion system. Gait data of healthy subjects according to different treadmill speeds and ages were matched to previous literature showing increased cadence and reduced step length for elderly subjects. Conclusion : Conclusively, 3D-IMU based shoes in gait analysis were a satisfactory alternative option in measuring linear gait parameters.

• Journal of the Korea Society of Computer and Information
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• v.15 no.4
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• pp.65-74
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• 2010

At the aim of solving the problems appearing in traditional optical motion capturing systems such as the interference among multiple patches and the complexity of sensor and patch allocations, this paper proposes a new motion capturing system which is composed of a single camera and multiple motion sensors. A motion sensor is consisted of an acceleration sensor and a gyro sensor to detect the motion of a patched body and the orientation (roll, pitch, and yaw) of the motion, respectively. Although Image information provides the positions of the patches in 2D, the orientation information of the patch motions acquired by the motion sensors can generate 3D pose of the patches using simple equations. Since the proposed system uses the minimum number of sensors to detect the relative pose of a patch, it is easy to install on a moving body and can be economically used for various applications. The performance and the advantages of the proposed system have been proved by the experiments.

• Journal of IKEEE
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• v.26 no.1
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• pp.133-136
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• 2022

This paper is about motion gesture recognition system, and proposes the following improvement to the flaws of the current system: a motion gesture recognition system and such algorithm that uses the video image of the entire hand and reading its motion gesture to advance the accuracy of recognition. The motion gesture recognition system includes, an image capturing unit that captures and obtains the images of the area applicable for gesture reading, a motion extraction unit that extracts the motion area of the image, and a hand gesture recognition unit that read the motion gestures of the extracted area. The proposed application of the motion gesture algorithm achieves 20% improvement compared to that of the current system.