• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2283-2286
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• 2003

This paper has expressed human's motion data into orthogonal parameters in low dimension, and created new motion data through this. We have reconstructed a new model consisting of orthogonal parameters from dividing human body data into three parts - hand, leg, and body to make new motions. Mixing these parts of body from different motions has leaded to new good motion data. It will be possible to use this motion editing not only for Animation Technology, but also for a three dimensional gesture recognition skill.

• Journal of the Korea Computer Graphics Society
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• v.25 no.2
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• pp.1-9
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• 2019

This study compares hand-based interfaces to improve a user's virtual reality (VR) presence by enhancing user immersion in VR interactions. To provide an immersive experience, in which users can more directly control the virtual environment and objects within that environment using their hands and, to simultaneously minimize the device burden on users using immersive VR systems, we designed two experimental interfaces (hand motion recognition sensor- and controller-based interactions). Hand motion recognition sensor-based interaction reflects accurate hand movements, direct gestures, and motion representations in the virtual environment, and it does not require using a device in addition to the VR head mounted display (HMD). Controller-based interaction designs a generalized interface that maps the gesture to the controller's key for easy access to the controller provided with the VR HMD. The comparative experiments in this study confirm the convenience and intuitiveness of VR interactions using the user's hand.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.1
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• pp.21-26
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• 2014

The focus of this paper is the designing a flexible three fingered hand system with 16 D.O.F for dynamic manipulation with an intelligent controller, and to build a useful database for dynamic manipulation based on the experimental results. The weight of the hand module is only 0.7 kg, but flexible motion and powerful grasping are possible. To achieve such a dynamic motion in a robotic hand, we have developed a flexible fingered hand with a control system incorporating image recognition system in which we deal with the problems of not only accuracy and range of motion but also the flexibility of hand. The fingers are arranged so as to grasp both circular and prismatic objects. In order to achieve the light mechanism, we reduced the number of joints and fingers as much as possible. We used three fingers, which is the minimum number to achieve a stable grasp.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.4
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• pp.183-189
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• 2018

The focus of this paper is to design and control a three fingered hand system with eight axes for smart factory with an flexible controller, and to keep a useful big database for dynamic manipulation based on the experimental results. The weight of the hand module is only 1.2 kg, but flexible motion and powerful grasping are possible. To achieve such a flexible motion control of a robotic hand, we have developed a robust and precise fingered hand with a control system incorporating image recognition system in which we deal with the problems of not only accuracy and range of motion but also the flexibility of hand. The fingers are arranged so as to grasp both circular and prismatic objects. In order to achieve the light mechanism, we reduced the number of joints and fingers as much as possible. In this study, it was used three fingers with eight axes which is the optimal number to achieve a robust grasping diverse shape parts for smart factory.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.6
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• pp.71-76
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• 2008

The focus of this paper is the designing a flexible three fingered hand system with 16 D.O.F for dynamic manipulation with an intelligent controller, and to build a useful database for dynamic manipulation based on the experimental results. The weight of the hand module is only 0.7 kg, but flexible motion and powerful grasping are possible. To achieve such a dynamic motion in a robotic hand, we have developed a flexible fingered hand with a control system incorporating image recognition system in which we deal with the problems of not only accuracy and range of motion but also the flexibility of hand. The fingers are arranged so as to grasp both circular and prismatic objects. In order to achieve the light mechanism, we reduced the number of joints and fingers as much as possible. We used three fingers, which is the minimum number to achieve a stable grasp.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.53-59
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• 2008

Recently, vision-based hand gesture recognition techniques have been developed for assisting elderly and disabled people to control home appliances. Frequently occurred problems which lower the hand gesture recognition rate are due to the inter-person variation and intra-person variation. The recognition difficulty caused by inter-person variation can be handled by using user dependent model and model selection technique. And the recognition difficulty caused by intra-person variation can be handled by using fuzzy logic. In this paper, we propose multivariate fuzzy decision tree learning and classification method for a hand motion recognition system for multiple users. When a user starts to use the system, the most appropriate recognition model is selected and used for the user.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.3
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• pp.1-10
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• 2010

As various interfacing devices for computational machines are being developed, a new HCI method using hand motion input is introduced. This interface method is a vision-based approach using a single camera for detecting and tracking hand movements. In the previous researches, only a skin color is used for detecting and tracking hand location. However, in our design, skin color and shape information are collectively considered. Consequently, detection ability of a hand increased. we proposed primary orientation edge descriptor for getting an edge information. This method uses only one hand model. Therefore, we do not need training processing time. This system consists of a detecting part and a tracking part for efficient processing. In tracking part, the system is quite robust on the orientation of the hand. The system is applied to recognize a hand written number in script style using DNAC algorithm. Performance of the proposed algorithm reaches 82% recognition ratio in detecting hand region and 90% in recognizing a written number in script style.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.2
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• pp.126-131
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• 2017

In this paper, we propose a method to extract meaningful motion among various kinds of hand gestures on giving commands to robots using hand gestures. On giving a command to the robot, the hand gestures of people can be divided into a preparation one, a main one, and a finishing one. The main motion is a meaningful one for transmitting a command to the robot in this process, and the other operation is a meaningless auxiliary operation to do the main motion. Therefore, it is necessary to extract only the main motion from the continuous hand gestures. In addition, people can move their hands unconsciously. These actions must also be judged by the robot with meaningless ones. In this study, we extract human skeleton data from a depth image obtained by using a Kinect v2 sensor and extract location data of hands data from them. By using the Kalman filter, we track the location of the hand and distinguish whether hand motion is meaningful or meaningless to recognize the hand gesture by using the hidden markov model.

• Journal of Korea Game Society
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• v.17 no.6
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• pp.113-120
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• 2017

With the development of virtual reality technology, in recent years, user-friendly hand gesture interface has been more studied for natural interaction with a virtual 3D object. Most earlier studies on the hand-gesture interface are using relatively simple hand gestures. In this paper, we suggest an intuitive hand gesture interface for interaction with 3D object in the virtual reality applications. For hand gesture recognition, first of all, we preprocess various hand data and classify the data through the binary decision tree. The classified data is re-sampled and converted to the chain-code, and then constructed to the hand feature data with the histograms of the chain code. Finally, the input gesture is recognized by MCSVM-based machine learning from the feature data. To test our proposed hand gesture interface we implemented a 'Virtual Block' game. Our experiments showed about 99.2% recognition ratio of 16 kinds of command gestures and more intuitive and user friendly than conventional mouse interface.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.120-122
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• 2004

Wearable input device that can make free-space typewriting possible is introduced. We named this device as $SCURRY^{TM}$. To measure the angular velocity of hand and the acceleration rates at the ends of fingers, we buried MEMS inertial sensors in this keyboard. We processed sensor signals to get the information on hand movement and finger-click motion. With this signal processing, apparent finger movements were depicted over the virtual keyboard shown on output device of a target computing system. In this paper, a finger-click recognition method is proposed to improve the recognition performance for finger clicking of $SCURRY^{TM}$. The proposed method is composed of three parts including feature extraction part, valid click part, and cross-talk avoidance part. The experiments were conducted to verify the effectiveness and efficiency of the proposed algorithms.