• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.105.2-105
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• 2001

This paper studies continuous Korean Sign Language (KSL) recognition using color vision. In recognizing gesture words such as sign language, it is a very difficult to segment a continuous sign into individual sign words since the patterns are very complicated and diverse. To solve this problem, we disassemble the KSL into 18 hand motion classes according to their patterns and represent the sign words as some combination of hand motions. Observing the speed and the change of speed of hand motion and using state automata, we reject unintentional gesture motions such as preparatory motion and meaningless movement between sign words. To recognize 18 hand motion classes we adopt Hidden Markov Model (HMM). Using these methods, we recognize 5 KSL sentences and obtain 94% recognition ratio.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2013.11a
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• pp.192-193
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• 2013

The purpose of this research is to comprehend experimentally the nature of human static load to wall for making use of the result as basic data to evaluate resisting force of lightweight wall. Human motions exerting static load are classified to 4 types, and two-hands pushing and shoulder pushing are defined as the instantaneously forcing motions with hands or shoulder put on the load plate, respectively. Back leaning and one-hand leaning are defined as motions of taking a rest in their respective comfortable posture. Measurement of static horizontal load caused by each motion showed that the highest load ratio depends on hardness of load plane and was 1.17~1.25 times of weight in two-hands pushing, 0.95~0.99 times in shoulder pushing, 0.16~0.18 times in back leaning, and 0.12~0.15 times in one-hand leaning.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.980-988
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• 2018

Motion estimation is a key Natural User Interface/Natural User Experience (NUI/NUX) technology to utilize motions as commands. HTC VIVE is an excellent device for estimating motions but only considers the positions of hands, not the orientations of arms. Even if the positions of the hands are the same, the meaning of motions can differ according to the orientations of the arms. Therefore, when the positions of arms are measured and utilized, their orientations should be estimated as well. This paper proposes a method for estimating the arm orientations based on the Bayesian probability of the hand positions measured in advance. In experiments, the proposed method was used to measure the hand positions with HTC VIVE. The results showed that the proposed method estimated orientations with an error rate of about 19%, but the possibility of estimating the orientation of any body part without additional devices was demonstrated.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.300-306
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• 2012

In this paper, we propose a vision based hand motion recognition method for an untouchable user interface of smart devices. First, an original color image is converted into a gray scaled image and its spacial resolution is reduced, taking the small memory and low computational power of smart devices into consideration. For robust recognition of hand motions through separation of horizontal and vertical motions, the horizontal principal area (HPA) and the vertical principal area (VPA) are defined respectively. From the difference images of the consecutively obtained images, the center of gravity (CoG) of the significantly changed pixels caused by hand motions is obtained, and the direction of hand motion is detected by defining the least mean squared line for the CoG in time. For verifying the feasibility of the proposed method, the experiments are carried out with a vision system.

• The Journal of Korea Robotics Society
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• v.1 no.2
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• pp.188-196
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• 2006

During the communication and interaction with a human using motions or gestures, a humanoid robot needs not only to look like a human but also to behave like a human to make sure the meanings of the motions or gestures. Among various human-like behaviors, arm motions of the humanoid robot are essential for the communication with people through motions. In this work, a mathematical representation for characterizing human arm motions is first proposed. The human arm motions are characterized by the elbow elevation angle which is determined using the position and orientation of human hands. That representation is mathematically obtained using an approximation tool, Response Surface Method (RSM). Then a method to generate human-like arm motions in real time using the proposed representation is presented. The proposed method was evaluated to generate human-like arm motions when the humanoid robot was asked to move its arms from a point to another point including the rotation of its hand. The example motion was performed using the KIST humanoid robot, MAHRU.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.1045-1050
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• 2005

This paper describes a design experience of a low-cost 6 DOF spatial tracker system where relative low accuracy and relatively long ranges, wireless communication will be achieved by means of low cost accelerometers and gyros with contemporary microprocessor. However, there are two key problems; one is the bias drift problem and the other is that single or double integration of acceleration signal suffers not only from noise but also from nonlinear effects caused by gravity. To be specific, beginning and stopping of hand motions needs to be accurately detected to initiate and terminate integration process to get position and pose of the hand from accelerometer and gyro signals, since errors due to noise and/or hand-shaking motions accumulated by integration processes. Several experimental results are shown to validate our proposed algorithms.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.4 s.235
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• pp.540-554
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• 2005

This paper presents a motion planning and control method for the dexterous manipulation with a robotic hand. For a given trajectory of an object, a simulation system calculates the necessary joint displacements and contact forces at the fingertip surfaces. These joint displacements and contact forces are the reference inputs to the control loops of the robotic fingers. A task is decomposed into a set of primitive motions, and each primitive motion is executed using the planned output of the simulation system as the reference. Force sensors and dynamic tactile sensors are used to adapt to errors and uncertainties encountered during manipulation. Several experimental results are presented.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.2
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• pp.61-70
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• 1997

Human-hand gestures have been used a means of communication among people for a long time, being interpreted as streams of tokens for a language. The signed language is a method of communication for hearing impaired person. Articulated gestures and postures of hands and fingers are commonly used for the signed language. This paper presents a system which recognizes the korean sign language (KSL) and translates the recognition results into a normal korean text and sound. A pair of data-gloves are used a sthe sensing device for detecting motions of hands and fingers. In this paper, we propose a dynamic gesture recognition mehtod by employing a fuzzy feature analysis method for efficient classification of hand motions, and applying a fuzzy min-max neural network to on-line pattern recognition.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.51-57
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• 2021

In this paper, we propose a new framework that calculates the user's hand motions using a Leap Motion device, and uses this to practice and analyze arm muscles as well as juggling motions. The proposed method can map the movement of the ball in a virtual environment according to the user's hand motions in real time, and analyze the amount of exercise by visualizing the relaxation and contraction of the muscles. The proposed framework consists of three main parts : 1) It tracks the user's hand position with the Leap Motion device. 2) As with juggling, the action pattern of the user throwing the ball is defined as an event. 3) We propose a parabola-based particle method to map the movement of a juggling shape to a ball based on the user's hand position. As a result, using the our framework, it is possible to play a juggling game in real-time.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.83.1-83
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• 2001

This paper presents a three-fingered robot hand, called the KIST hand, Which have one active joint and one passive joint. The thumb is fixed on the palm, and the index and the middle take lateral motions symmetrically. A mechanical clutch and an embedded force sensor, attached on the distal link of the fingers, enable the KIST hand to perform human-like functions. A result of experiment shows reliable grasping performance of the hand which maintain stable grasp under disturbances.