• International Journal of Contents
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• v.12 no.2
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• pp.31-36
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• 2016

The purpose of this research is to realize interactive art based on user's motions information using real time internet search terms. For this purpose, real-time search terms and related news information were extracted from three domestic and foreign portal sites, and the extracted information was used to generate content for interaction with the user. For interaction between the generated content and the user, a motion-based interactive technology that optimizes the intentions and experiences of the user was developed. A motion-based interactive system can be used to develop an immersive interface that induces user interest.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.552-555
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• 2012

The main goal of this paper is to develop a robust visual tracking algorithm with particle filtering. Visual Tracking with particle filter technique is not easy task due to cluttered environment, illumination changes. To deal with these problems, we develop an efficient observation model for target tracking with particle filter. We develop a robust phase correlation combined with motion information based observation model for particle filter framework. Phase correlation provides straight-forward estimation of rigid translational motion between two images, which is based on the well-known Fourier shift property. Phase correlation has the advantage that it is not affected by any intensity or contrast differences between two images. On the other hand, motion cue is also very well known technique and widely used due to its simplicity. Therefore, we apply the phase correlation integrated with motion information in particle filter framework for robust tracking. In experimental results, we show that tracking with multiple cues based model provides more reliable performance than single cue.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.3
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• pp.139-148
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• 2022

In this paper, we implement a distributed FMCW MIMO radar system to obtain Micro Doppler signatures of target motions. In addition, we also develop federated learning based motion recognition algorithm based on the Micro-Doppler radar signature collected by the implemented FMCW MIMO radar system. Through the experiment, we have verified that the proposed federated learning based algorithm can improve the motion recognition accuracy up to 90%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.419-420
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• 2022

This paper presents a method that allows users to interactively register their own gestures for a motion-based game system. Existing motion-based game systems create recognizers by collecting predefined gesture data. However, this sometimes requires difficult expertise or rather difficult courses. To alleviate these complex situations, we propose a full-body skeleton-based game system that can interactively register gestures.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.1655-1656
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• 2013

• Science of Emotion and Sensibility
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• v.14 no.2
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• pp.221-226
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• 2011

Although diverse researches on sensing method of human movement have been performed, there are still many limitations to the existing methods. As a part of supplementing the limitations to the existing motion sensing methods, this study aimed to execute an exploratory examination on a POF-based sleeve-shaped motion sensor for less restrictive sensing of human movement. In this study, a set of POF-based motion sensor, which was embedded in a sleeve-shaped platform was devised, and a set of exploratory experiments was performed on the possibility of sensing of human movement as diverse as in daily life, through this device. The scope of this research was limited to an exploration on the possibility and basic elements of POF-based sleeve-shaped motion sensor, while the influence of sleeve patterns, those of wearer's somatotype, those of sewing method were not studied in this study. When compared to the pre-existing methods, the POF-based motion sensor platformed on sleeve in this study, which was purposively devised to be applied to the motion sensing clothing shows some beneficial characteristics : more sensitive measurement on human motion, low cost, no timely restriction in sensing, no request for gigantic apparatus and space for sensing.

• 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.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.345-352
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• 2024

We are designed to solve cyber motion sickness, an important task that must be addressed for the growth of the virtual reality content industry. Not only the industry but also academia are paying a lot of attention. However, despite long interest and research on the phenomenon of cyber motion sickness, a solution has not been drawn. This is deeply related to the lack of tools that can effectively measure cyber motion sickness. Therefore, in this paper, prior studies on cyber motion sickness were analyzed to develop a tool that can effectively measure cyber motion sickness when users experience immersive virtual reality. The measurement method of cyber motion sickness used in previous studies, each characteristic and limitation, and common factors related to cyber motion sickness were analyzed. Each of the related factors was derived as sub-factors. Based on the analyzed contents, an effective cyber motion sickness measurement evaluation tool model in immersive virtual reality was presented. It is expected that the evaluation tool model can be used for the study of cyber motion sickness.

• Journal of the Korea Computer Graphics Society
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• v.29 no.5
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• pp.11-20
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• 2023

In this paper, we propose a novel deep learning-based motion reconstruction approach that facilitates the generation of full-body motions, including finger motions, while also enabling the online adjustment of motion generation delays. The proposed method combines the Vive Tracker with a deep learning method to achieve more accurate motion reconstruction while effectively mitigating foot skating issues through the use of an Inverse Kinematics (IK) solver. The proposed method utilizes a trained AutoEncoder to reconstruct character body motions using tracker data in real-time while offering the flexibility to adjust motion generation delays as needed. To generate hand motions suitable for the reconstructed body motion, we employ a Fully Connected Network (FCN). By combining the reconstructed body motion from the AutoEncoder with the hand motions generated by the FCN, we can generate full-body motions of characters that include hand movements. In order to alleviate foot skating issues in motions generated by deep learning-based methods, we use an IK solver. By setting the trackers located near the character's feet as end-effectors for the IK solver, our method precisely controls and corrects the character's foot movements, thereby enhancing the overall accuracy of the generated motions. Through experiments, we validate the accuracy of motion generation in the proposed deep learning-based motion reconstruction scheme, as well as the ability to adjust latency based on user input. Additionally, we assess the correction performance by comparing motions with the IK solver applied to those without it, focusing particularly on how it addresses the foot skating issue in the generated full-body motions.

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