• Proceedings of the Korea Society for Simulation Conference
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• 1998.10a
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• pp.120-123
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• 1998

In animating an articulated entity with motion capture data, especially when the reconstruction is based on forward kinematics, there could be large discrepancies at the end effector. The small errors in joint angles tend to be amplified as the forward kinematics positioning progresses toward the end effector. In this paper, we present an algorithm that enhances the motion capture data to reduce positional errors at the end effector. The process is optimized so that the characteristics of the original joint angle data is preserved in the resulting motion. The frames at which the end-effector position needs to be accurate are designated as“keyframes”(e.g. starting and ending frames). In the algorithm, corrections by inverse kinematics are performed at sparse keyframes and they are interpolated with a cubic spline which produces a curve best approximating the measured joint angles. The experiment proves that our algorithm is a valuable tool to improve measured motion especially when end-effector trajectory contains a special goal.

• Journal of the Korean Society of Safety
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• v.29 no.1
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• pp.41-46
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• 2014

The design of a 7 degree of freedom motion capture device(MCD) has been presented. The newly designed MCD overcomes the shortcomings of the existing CADEN-7 exoskeleton robot by implementing various ergonomic design. To improve ease of operation, light-weight high-strength materials such as carbon pipes and engineering plastics were used to reduce weight of the MCD and arm-length adjustment mechanism was also added. The MCD showed consistent measurement results in designed experiments involving change of arm posture from nominal configuration to either elbow-side or arm-front configurations. Furthermore, captured motion in more natural tennis swing appeared to agree well with visual observations made.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.47-54
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• 2024

With the rapid development of 3D animation, MetaHuman is widely used in film production, game development and VR production as a virtual human creation platform.In the animation production of virtual humans, motion capture is usually used.Since different motion capture solutions use different skeletons for motion recording, when the skeleton level of recorded animation data is different from that of MetaHuman, the animation data recorded by motion capture cannot be directly used on MetaHuman. This requires Reorient the skeletons of both.This study explores an efficient skeleton reorientation method that can maintain the accuracy of animation data by reducing the number of bone chains.In the experiment, three skeleton structures, Rokoko, Mixamo and Xsens were used for efficient redirection experiments, to compare and analyze the adaptability of different skeleton structures to the MetaHuman skeleton, and to explore which skeleton structure has the highest compatibility with the MetaHuman skeleton.This research provides an efficient skeleton reorientation idea for the production team of 3D animated video content, which can significantly reduce time costs and improve work efficiency.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1625-1628
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• 2003

Recently the VR technique has evolved into a mixed reality (MR) technique, in which a user can observe a real world in front of him/her as well as virtual objects displayed. This has been realized by the employment of a see-through type HMD (S-HMD). We have been developing a mixed reality space employing the MR technique. The objective of our study is to realize a virtual human that acts as a man-machine interface in the real space. It is important in the study to create a virtual human acting naturally in front of a user. In order to give natural motions to the virtual human, we employ a developed motion capture technique. We have already created various 3-D human motion models by the motion capture technique. In this paper, we present a technique for creating a virtual human using a human model provided by a computer graphics software, 3D Studio Max(C). The main difficulty of this issue is that 3D Studio Max(C) claims 28 feature points for describing a human motion, but the used motion capture system assumes less number of feature points. Therefore a technique is proposed in the paper for producing motion data of 28 feature points from the motion data of less number of feature points or from incomplete motion data. Performance of the proposed technique was examined by observing visually the demonstration of some motions of a created virtual human and overall natural motions were realized.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.8
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• pp.756-760
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• 2010

In this paper, a new method to recognize various motions of fighting with an aid of HMM is proposed. There are four kinds of fighting motion such as hook, jab, uppercut, and straight as the fighting motion. The motion graph is generalized to define each motion in motion data and the new 3D-chain code is used to convert motion data to motion graphs. The recognition experiment has been performed with HMM algorithm on motion graphs. The motion data is captured by a motion capture system developed in this study and by five actors. Experimental results are given with relatively high recognition rate of at least 85%.

• The KIPS Transactions:PartB
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• v.15B no.2
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• pp.103-112
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• 2008

Image-based motion capture technology is often used in making realistic computer animation. In this paper we try to implement image-based motion rendering by fixing a camera to a PC. Existing image-based rendering algorithms have disadvantages of high computational burden or low accuracy. The former disadvantage causes too long making-time of an animation. The latter disadvantage degrades reality in making realistic animation. To compensate for those disadvantages of the existing approaches, this paper presents an image-based motion rendering algorithm with low computational load and high estimation accuracy. In the proposed approach, an incremental motion rendering algorithm with low computational load is analyzed in the respect of optimal control theory and revised so that its estimation accuracy is enhanced. If we apply this proposed approach to optic motion capture systems, we can obtain additional advantages that motion capture can be performed without any markers, and with low cost in the respect of equipments and spaces.

• Journal of Broadcast Engineering
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• v.25 no.4
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• pp.528-536
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• 2020

As humanoid robot technology advances, the use of robots for performance is increasing. As a result, studies are being conducted to increase the scope of use of robots in performances by making them natural like humans. Among them, the use of motion capture technology is often used, and there are environmental inconveniences in preparing for motion capture, such as the need for IMU sensors or markers attached to each part of the body and precise high-performance cameras. In addition, for robots used in performance technology, there is a problem that they have to respond in real time depending on the unexpected situation or the audience's response. To make up for the above mentioned problems, in this paper, we proposed a real-time motion capture system by using a number of RGB-D cameras and creating natural robot motion similar to human motion by using motion-captured data.

• Journal of KIISE:Software and Applications
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• v.30 no.11
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• pp.1092-1101
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• 2003

Most of 3D character animation adjusts the gait of their characters for various terrains, using motion capture data through the motion capture equipments. This motion capture data can be naturally presented as real human motions, which are to be adjusted according to the various types of terrain. In addition, there would be a difficulty applying motion capture data for other characters in which the motion data will be captured again or edited for the existing motion data. Therefore, this paper proposes a method that is to generate walking motion for various terrains, such as flat, inclined plane, stair, and irregular face, and a method that is to calculate the trajectory of the swing leg and pelvis. These methods are able to generate various gaits controlled by the parameters of body height, walking speed, stride, etc. In addition, the positions and angles of joint can be calculated by using inverse kinematics, and the cubic spline will be used to calculate the trajectory of the joint.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.3_1spc
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• pp.558-565
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• 2013

This paper describes a whole-body (human body's) motion generation scheme for an android robot that uses motion capture device and a nonlinear constrained optimization method. Because the captured motion data are based on global coordinates and the actors have different heights and different upper-lower body ratios, the captured motion data cannot be used directly for a humanoid robot. In this paper, we suggest a method for obtaining robot joint angles, which allow the resultant robot motion to be as close as possible to the captured human motion data, by applying a nonlinear constrained optimization method. In addition, the results are animated to demonstrate the similarity of the motions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4624-4644
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• 2019

With the development of films, games and animation industry, analysis and reuse of human motion capture data become more and more important. Human motion segmentation, which divides a long motion sequence into different types of fragments, is a key part of mocap-based techniques. However, most of the segmentation methods only take into account low-level physical information (motion characteristics) or high-level data information (statistical characteristics) of motion data. They cannot use the data information fully. In this paper, we propose an unsupervised framework using both low-level physical information and high-level data information of human motion data to solve the human segmentation problem. First, we introduce the algorithm of CFSFDP and optimize it to carry out initial segmentation and obtain a good result quickly. Second, we use the ACA method to perform optimized segmentation for improving the result of segmentation. The experiments demonstrate that our framework has an excellent performance.