• Journal of Institute of Control, Robotics and Systems
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• v.17 no.4
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• pp.368-374
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• 2011

This paper proposes a robot control human interface using Markov model (HMM) based hand signal recognizer. The command receiving humanoid robot sends webcam images to a client computer. The client computer then extracts the intended commanding hum n's hand motion descriptors. Upon the feature acquisition, the hand signal recognizer carries out the recognition procedure. The recognition result is then sent back to the robot for responsive actions. The system performance is evaluated by measuring the recognition of '48 hand signal set' which is created randomly using fundamental hand motion set. For isolated motion recognition, '48 hand signal set' shows 97.07% recognition rate while the 'baseline hand signal set' shows 92.4%. This result validates the proposed hand signal recognizer is indeed highly discernable. For the '48 hand signal set' connected motions, it shows 97.37% recognition rate. The relevant experiments demonstrate that the proposed system is promising for real world human-robot interface application.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.1
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• pp.47-55
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• 2017

As preliminary work for the establishment of a harmonized ship hand signal standard, this paper explores the availability of hand signals as a means of shipboard work communication and considers the validity of standardization. Prior to the feasibility study, shipboard work activities that use hand signals were classified based only on ship safety managers' arbitrary decisions. This survey was carried out to measure shipboard workers' willingness to communicate with hand signals and their preferences regarding the institutional standardization of a hand signal framework if they engage in activities classified as relevant. The results of statistical analysis (a t-test and correlation analysis) showed that respondents are willing to accept harmonized hand signals regardless of both their work type (crew/safety supervisors) and work department (deck/engine room) under working situations where hand signals are an available means of communication. In addition, there was a significant difference in the extent of shipboard workers' frequency of hand signal usages between each type of work activity, indicating a significant positive (+) correlation between frequency of usage and preference for standardization. Finally, it was concluded that shipboard work communication would be effectively improved if a follow-up study is carried out to establish prioritized harmonized hand signal standards for port-related work activities, such as crane operation, windlass/winch operation, line movement/delivery and cargo hold operations.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.30-37
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• 2011

This paper proposes a language set of hand motions for enhancing the performance of vision-based hand signal recognizer. Based on the statistical analysis of the angular tendency of hand movements in sign language and the hand motions in practical use, we construct four motion primitives as building blocks for basic hand motions. By combining these motion primitives, we design a discernable 'fundamental hand motion set' toward increasing the hand signal recognition. To demonstrate the validity of proposed designing method, we develop a 'fundamental hand motion set' recognizer based on hidden Markov model (HMM). The recognition system showed 99.01% recognition rate on the proposed language set. This result validates that the proposed language set enhances discernaility among the hand motions such that the performance of hand signal recognizer is improved.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.3
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• pp.103-114
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• 2004

This paper deals with a system that is capable of recognizing hand-signals in 3-dimensional space. The system uses 2 color cameras as input devices. Vision-based gesture recognition system is known to be user-friendly because of its contact-free characteristic. But as with other applications using a camera as an input device, there are difficulties under complex background and varying illumination. In order to detect hand region robustly from a input image under various conditions without any special gloves or markers, the paper uses previous position information and adaptive hand color model. The paper defines a hand-signal as a combination of two basic elements such as 'hand pose' and 'hand trajectory'. As an extensive classification method for hand pose, the paper proposes 2-stage classification method by using 'small group concept'. Also, the paper suggests a complementary feature selection method from images from two color cameras. We verified our method with a hand-signal application to our driving simulator.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.215-218
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• 2002

Gesture recognitions needed for various applications and is now gaining in importance as one method of enabling natural and intuitive human machine communication. In this paper, we propose a real time hand-signal recognition system in 3-dimensional space performs robust, real-time tracking under varying illumination. As compared with the existing method using classical pattern matching, this system is efficient with respect to speed and also presents more systematic way of defining hand-signals and developing a hand-signal recognition system. In order to verify the proposed method, we developed a virtual driving system operated by hand-signals.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.3C
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• pp.217-223
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• 2012

In this paper, we would like to propose techniques to analyze effect according to stimulation kidney associated hand acupuncture by applying technique to measure changes of facial image and voice signal. To this end, we measured color change of JIGAK(jaw) area associated kidney in facial image and voice signal stimulation before and after of kidney associated hand acupuncture. In addition, we measured changes of the first formant frequency bandwidth and Shimmer to element of voice signal analysis in connection with kidney in experiment. We can be measured reduction of the first formant frequency bandwidth and Shimmer, black of JIGAK area according to stimulation of kidney associated hand acupuncture. Finally, we would like to demonstrate objective effect of kidney associated hand acupuncture through the analysis of statistical significance by measurement techniques of facial image and voice signal.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.474-474
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• 2000

This paper shows that a system with two-link arm can obtain hand reaching movement to a target object projected on a visual sensor by reinforcement learning using a layered neural network. The reinforcement signal, which is an only signal from the environment, is given to the system only when the hand reaches the target object. The neural network computes two joint torques from visual sensory signals, joint angles, and joint angular velocities considering the urn dynamics. It is known that the trajectory of the voluntary movement o( human hand reaching is almost straight, and the hand velocity changes like bell-shape. Although there are some exceptions, the properties of the trajectories obtained by the reinforcement learning are somewhat similar to the experimental result of the human hand reaching movement.

• Proceedings of the KIPE Conference
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• 2010.07a
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• pp.265-266
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• 2010

This paper propose the test method for performance of myoelectric hand prosthesis(MHP) according to myoelectric signal generated in the human muscle. The MHP consists of a mechanical hand, a surface myoelectric sensor(SMES) for measuring myoelectric signal, a control system and a charging battery. The propose test method is proved the reliability of MHP.

• The Journal of Korea Robotics Society
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• v.11 no.2
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• pp.100-107
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• 2016

To realize a robot hand interacting like a human hand, there are many tactile sensors sensing normal force, shear force, torque, shape, roughness and temperature. This sensing signal is essential to manipulate object accurately with robot hand. In particular, slip sensors make manipulation more accurate and breakless to object. Up to now several slip sensors were developed and applied to robot hand. Many of them used complicate algorithm and signal processing with vibration data. In this paper, we developed novel principle slip sensor using separation layer. These two layers are moved from each other when slip occur. Developed sensor can sense slip signal by measuring this relative displacement between two layers. Also our principle makes slip signal decoupled from normal force and shear force without other sensors. The sensor was fabricated using the NBR(acrylo-nitrile butadiene rubber) and the Ecoflex as substrate and a paper as dielectric. To verify our sensor, slip experiment and normal force decoupling test were conducted.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1223-1228
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• 2018

LTE-R(Long Term Evolution - Railway), as a mobile communication technology to support safety operation of train on high speed railway system, have to be equipped appropriately by hand-over method for high moving environment of train. In this paper, hand-over performance of LTE-R network, which is used in railway communication system, is analyzed and hand-over implementation condition is suggested with this analysis. The performance analysis of this study is carried out with computer simulation with NS(Network Simulator)-3. SINR(Signal to Interference and Noise Ratio) and RSRP(Reference Signal Received Power), and Data Rate is used for hand-over performance parameter.