• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.185-188
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• 2017

Health promotion is essential for overcoming the low health longevity of senior citizens preparing for aging population. Therefore, the lower body strengthening exercise to prevent falls is crucial to prevent a fall in the number of deaths of senior citizens. In this game model, the elderly are aiming at home training contents that can be found to feel that the elderly are going out of walk and exercising in the natural environment. To achieve this, Kinect extracts a specific bone model provided by the Kinect Sensor to generate the feature vectors and recognizes the movements and motion of the user.

• Journal of the Korea Computer Graphics Society
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• v.23 no.1
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• pp.33-38
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• 2017

In this paper, we suggest a method to simulate high-quality iguana animation by using low-quality motion capture data. Iguana motion data captured using a small number of markers cannot express its movement precisely, and even with a realistic skin mesh, it shows unnatural movement because of limited degrees of freedom. In order to solve this problem, we propose to simulate a natural and flexible movement by applying a soft-body simulation technique which models the movement of an iguana according to muscle forces and body's elastic forces. We construct a motion graph from the motion capture data to describe the iguana's various movements, and utilize it to select appropriate movements when the iguana moves. A target point on a terrain is set from the user's input, and a graph path is planned based on it. As a result, the input movement of iguana walking on a flat ground transforms to a movement that is adapted in an online manner to the irregular heights of the terrain. Such a movement is used to calculate the ideal muscle lengths that are needed for soft-body simulation. Lastly, a tetrahedral mesh of the iguana is physically simulated to adapt to various situations by applying a soft-body simulation technique.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2095-2102
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• 2017

In this paper, we implemented the elderly home training contents provide individual exercise prescription according to the user's athletic ability and provide personalized program to the elderly individual. Health promotion is essential for overcoming the low health longevity of senior citizens preparing for aging population. Therefore, the lower body strengthening exercise to prevent falls is crucial to prevent a fall in the number of deaths of senior citizens. In this game model, the elderly are aiming at home training contents that can be found to feel that the elderly are going out of walk and exercising in the natural environment. To achieve this, Kinect extracts a specific bone model provide by the Kinect Sensor to generate the feature vectors and recognizes the movements and motion of the user. The recognition test using the Kinect sensor showed a recognition rate of about 80 to 97%.

• Journal of the HCI Society of Korea
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• v.3 no.1
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• pp.33-38
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• 2008

The major users of children's library are children and housewives. Recent increasing frequency of their visit to the library expands the function of it from the place where they borrow and read books further to the cultural space where each family unit can enjoy leisure activities. Though the children's library basically is a quiet place for reading books, peers' establishing friendship and emotional bond with the parents, and such plays as small scale muscular movements take place in addition to reading activities because the major users are infants under six or children in the lower grades in elementary school. Thus, in order to study the features and requirements that are inherent in the various behaviors of the children who use furniture, understanding of the particular factors in the physical environment of the children's library and the user context must precede. In reality, though the fixed form of the desks and chairs in the library was made by a small number of designers, a large number of children are using them in tremendously various ways beyond the ways that the designers had intended, adapting themselves to the environmental context. Therefore, the purpose of this study is to find out the children's using way of seats when they do reading and playing activities based on the way of interaction between children and parents, and, after modeling of the children's behavior data, to understand the demands inherent inside the various behaviors of children who use furniture.

• 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.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1627-1633
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• 2017

Human dance is difficult to learn since there is no effective way to imitate an expert's motion, a sequence of complicated body movements, without taking an actual class. In this paper, we propose a dance learning system using human depth information. In the proposed system, a set of example motions are captured from various expert dancers through a marker-free motion capture and archived into a motion database server for online dance lessons. Given the end-user devices such as tablet and kiosk PCs, a student can learn a desired motion selected from the database and send one's own motion to an instructor for online feedback. During this learning process, our system provides a posture-based motion search and multi-mode views to support the efficient exchange of motion data between the student and instructor under a networked environment. The experimental results demonstrate that our system is capable to improve the student's dance skills over a given period of time.

• Journal of the Korea Society of Computer and Information
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• v.26 no.7
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• pp.45-55
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• 2021

Information obtained through various sensors embedded in a smartphone can be used to identify and analyze user's movements and situations. In this paper, we propose two rule-based motion detection systems that can detect three alphabet motions, 'I', 'S', and 'Z' by analyzing data obtained by the acceleration and gyroscope sensors in a smartphone. First of all, the characteristics of acceleration and angular velocity for each motion are analyzed. Based on the analysis, two rule-based systems are proposed and implemented as an android application and it is used to verify the detection performance for each motion. Two rule-based systems show high recognition rate over 90% for each motion and the rule-based system using ensemble shows better performance than another one.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.1
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• pp.27-35
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• 2022

In the most IPS (Indoor Positioning System), it is available to specify the user's movement by sending a specific signal from a tag such as a beacon to multiple receivers. This method is very efficiently used in places where the number of people is limited. On the other hand, in large commercial facilities, it is nearly difficult to apply the existing IPS method because it is necessary to attach a tag to each customer. In this paper, we propose a system that uses an external sensor grid to identify people's movement without using tags. Each sensor node uses both an ultrasonic sensor and an infrared sensor to monitor people's movements and sends collected data to the main server through wireless transmission for easy system maintenance. The operation was verified using the FPGA board, and we designed a VLSI circuit in 180nm process.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1223-1230
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• 2020

Due to the aging of the population, the number of the elderly is increasing, and the nuclear family is rapidly progressing. Today's AI speakers respond to user's commands rather than conversations that occur on a daily basis. If the elderly living alone do not talk first, the usability of the AI speaker will decrease. In this paper, it describes the development of AI speakers for active interaction tailored to the aged. This speaker can identify the movements of the elderly who live alone and their surroundings, actively speak to them, and display emotional expressions appropriate to the content of the conversation. Through this, users will be able to anthropomorphize AI speakers, so they can feel familiarity and emotional conversation is expected to play a positive role in easing their loneliness.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.212-220
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• 2013

Recently, there has been tremendous increase in human-computer/machine interaction system, where the goal is to provide with an appropriate service to the user at the right time with minimal human inputs for human augmented cognition system. To develop an efficient human augmented cognition system based on human computer/machine interaction, it is important to interpret the user's implicit intention, which is vague, in addition to the explicit intention. According to cognitive visual-motor theory, human eye movements and pupillary responses are rich sources of information about human intention and behavior. In this paper, we propose a novel approach for the identification of human implicit visual search intention based on eye movement pattern and pupillary analysis such as pupil size, gradient of pupil size variation, fixation length/count for the area of interest. The proposed model identifies the human's implicit intention into three types such as navigational intent generation, informational intent generation, and informational intent disappearance. Navigational intent refers to the search to find something interesting in an input scene with no specific instructions, while informational intent refers to the search to find a particular target object at a specific location in the input scene. In the present study, based on the human eye movement pattern and pupillary analysis, we used a hierarchical support vector machine which can detect the transitions between the different implicit intents - navigational intent generation to informational intent generation and informational intent disappearance.