• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3136-3150
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• 2015

A vision-based 3D tracking of articulated human hand is one of the major issues in the applications of human computer interactions and understanding the control of robot hand. This paper presents an improved approach for tracking and recovering the 3D position and orientation of a human hand using the Kinect sensor. The basic idea of the proposed method is to solve an optimization problem that minimizes the discrepancy in 3D shape between an actual hand observed by Kinect and a hypothesized 3D hand model. Since each of the 3D hand pose has 23 degrees of freedom, the hand articulation tracking needs computational excessive burden in minimizing the 3D shape discrepancy between an observed hand and a 3D hand model. For this, we first created a 3D hand model which represents the hand with 17 different parts. Secondly, Random Forest classifier was trained on the synthetic depth images generated by animating the developed 3D hand model, which was then used for Haar-like feature-based classification rather than performing per-pixel classification. Classification results were used for estimating the joint positions for the hand skeleton. Through the experiment, we were able to prove that the proposed method showed improvement rates in hand part recognition and a performance of 20-30 fps. The results confirmed its practical use in classifying hand area and successfully tracked and recovered the 3D hand pose in a real time fashion.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.6
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• pp.593-598
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• 2014

Hand gesture recognition based on vision is a challenging task in human-robot interaction. The sign language of finger spelling alphabets has been tested as a kind of hand gesture. In this paper, we test hand gesture recognition by detecting the contour shape and orientation of hand with visual image. The method has three stages, the first stage of finding hand component separated from the background image, the second stage of extracting the contour feature over the hand component and the last stage of comparing the feature with the reference features in the database. Here, finger spelling alphabets are used to verify the performance of our system and our method shows good performance to discriminate finger alphabets.

• Journal of Information Processing Systems
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• v.8 no.3
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• pp.399-408
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• 2012

Hand gesture recognition is an important area of research in the field of Human Computer Interaction (HCI). The geometric attributes of the hand play an important role in hand shape reconstruction and gesture recognition. That said, fingertips are one of the important attributes for the detection of hand gestures and can provide valuable information from hand images. Many methods are available in scientific literature for fingertips detection with an open hand but very poor results are available for fingertips detection when the hand is closed. This paper presents a new method for the detection of fingertips in a closed hand using the corner detection method and an advanced edge detection algorithm. It is important to note that the skin color segmentation methodology did not work for fingertips detection in a closed hand. Thus the proposed method applied Gabor filter techniques for the detection of edges and then applied the corner detection algorithm for the detection of fingertips through the edges. To check the accuracy of the method, this method was tested on a vast number of images taken with a webcam. The method resulted in a higher accuracy rate of detections from the images. The method was further implemented on video for testing its validity on real time image capturing. These closed hand fingertips detection would help in controlling an electro-mechanical robotic hand via hand gesture in a natural way.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.5
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• pp.14-20
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• 2006

In recent year, as the robot technology is developed, the researches on the artificial muscle actuator that enables robot to move dexterously like biological organ become active. Actuators are key technologies underpinning robotics. Breakthroughs in actuator technology, particular in terms of power-to-weight ratio, or energy-density, will have significant impacts upon the design and control of robotic system. In this paper, a new approach to design and control of shape memory alloy(SMA) actuator is presented to drive the robot hand. SMA wire is divided into many segments and their thermal states of the SMA are controlled individually in a binary manner. This control manner will reduce the hysteresis that the SMA material has and it becomes the fundamental technology to develop the anthropomorphic robot hand. In this paper, the mechanism In the digital step motor of the shape memory alloy that is driven by the segmented binary control, which is a new control technique, is studied. This SMA digital step actuator applies for the robot hand and the driving mechanism of the robot hand is investigated.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.341-345
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• 2009

We present an augmented reality (AR) application for cell phone where users put a virtual pet on their palms and play/interact with the pet by moving their hands and fingers naturally. The application is fundamentally based on hand/palm pose recognition and finger motion estimation, which is the main concern in this paper. We propose a fast and efficient hand/palm pose recognition method which uses natural features (e.g. direction, width, contour shape of hand region) extracted from a hand image with prior knowledge for hand shape or geometry (e.g. its approximated shape when a palm is open, length ratio between palm width and pal height). We also propose a natural interaction method which recognizes natural motion of fingers such as opening/closing palm based on fingertip tracking. Based on the proposed methods, we developed and tested the AR application on an ultra-mobile PC (UMPC).

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.4
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• pp.309-318
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• 2001

In this paper, we describe methods that analyze a human gesture. A human interface(HI) system for analyzing gesture extracts the head and hand regions after taking image sequence of and operators continuous behavior using CCD cameras. As gestures are accomplished with operators head and hands motion, we extract the head and hand regions to analyze gestures and calculate geometrical information of extracted skin regions. The analysis of head motion is possible by obtaining the face direction. We assume that head is ellipsoid with 3D coordinates to locate the face features likes eyes, nose and mouth on its surface. If was know the center of feature points, the angle of the center in the ellipsoid is the direction of the face. The hand region obtained from preprocessing is able to include hands as well as arms. For extracting only the hand region from preprocessing, we should find the wrist line to divide the hand and arm regions. After distinguishing the hand region by the wrist line, we model the hand region as an ellipse for the analysis of hand data. Also, the finger part is represented as a long and narrow shape. We extract hand information such as size, position, and shape.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.1
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• pp.68-72
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• 2015

Ultrasonic inspection robot systems have been widely researched and developed for the real-time monitoring of structures such as power plants. However, an inspection robot that is operated in a simple pattern has limitations in its application to various structures in a plant facility because of the diverse and complicated shapes of the inspection objects. Therefore, accurate control of the robot is required to inspect complicated objects with high-precision results. This paper presents the idea that the shape and movement information of an ultrasonic inspector's hand could be profitably utilized for the accurate control of robot. In this study, a polymer flex sensor was applied to monitor the shape of a human hand. This application was designed to intuitively control an ultrasonic inspection robot. The movement and shape of the hand were estimated by applying multiple sensors. Moreover, it was successfully shown that a test robot could be intuitively controlled based on the shape of a human hand estimated using polymer flex sensors.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.768-771
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• 1997

Geometric probing addresses the problem of determining geometric aspects of a structure from the mathematics and results of a physical measuring device such as a probe. This paper presents a new algorithm to recognize the shape of an unknown object by using a robot hand with a force and torque sensor. The new algorithm is called S.E.P.(Shape Exploration Procedure) which finds the global shape of an unknown object. The proposed method is composed of three major parts, finding contact informations such as contact point, calculation of shape information such as curvature, and expression of global shape from these informations. Comparing with the conventional approaches, the advantages of the proposed method are explained and verified by conducting experiments with a 3-dof SCARA robot.

• Korean Journal of Human Ecology
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• v.13 no.6
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• pp.1023-1029
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• 2004

In the current study, we measured the hands and other representative body items of 223 elementary school girls using Martin Anthropometer and a digital camera so that we would be able to provide information on both size and shape of hands for design of hand-related products. As time goes on, hands get bigger, yet they get thinner at the same time. The data implies that the frame of hands grows, but the skin fat lessens, which could be a determinant factor in the size system of hand-related products. According to the results of a factor analysis on 26 hand items, 5 factors including hand laterality and linearity, fingertip shape, finger breadth, and hand depth, have been extracted. Pearson's correlation showed that most of hand-related factors were strongly associated with other body items. Finger breadth and hand depth, however, were found less related to other body items. The ANOVA test used in testing the difference of hand factors showed, in most items, a difference by ages, but there was no significant differences in fingertip breadth, the third factor, Interestingly, in hand depth, the fifth factor, lower grade girls' hands were thicker than higher grade girls'. This research suggests that the size system of uniformly increasing the size of all hand parts by age groups should be reconsidered and leaves much for improvement.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.10 s.181
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• pp.2461-2468
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• 2000

In this paper, single fiber pull-out test is used to measure the interfacial bonding shear strength of $Ti_{50}-Ni_{50}$ shape memory alloy composite with temperature. Fiber and matrix of $Ti_{50}-Ni_{50}$ shape memory alloy composite are respectively $Ti_{50}-Ni_{50}$ shape memory alloy and epoxy resin. To strengthen the interfacial bonding shear stress, various surface treatments are used. They are the hand-sanded surface treatment, the acid etched surface treatment and the silane coupled surface treatment etc.. The interfacial bonding shear strength of surface treated shape memory alloy fiber is greater than that of surface untreated shape memory alloy fiber by from 10% to 16%. It is assured that the hand-sanded surface treatment and the acid etched surface treatment are the best way to strengthen the interfacial bonding shear strength of $Ti_{50}-Ni_{50}$ shape memory composite. The best treatment condition of surface is 10% HNO$_3$ solution in the etching method to strengthen the interfacial bonding shear strength of $Ti_{50}-Ni_{50}$ shape memory alloy composite.