• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.319-327
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• 2012

In this paper, we present a sign language recognition model which does not use any wearable devices for object tracking. The system design issues and implementation issues such as data representation, feature extraction and pattern classification methods are discussed. The proposed data representation method for sign language patterns is robust for spatio-temporal variances of feature points. We present a feature extraction technique which can improve the computation speed by reducing the amount of feature data. A neural network model which is capable of incremental learning is described and the behaviors and learning algorithm of the model are introduced. We have defined a measure which reflects the relevance between the feature values and the pattern classes. The measure makes it possible to select more effective features without any degradation of performance. Through the experiments using six types of sign language patterns, the proposed model is evaluated empirically.

• Journal of the Korea Society of Computer and Information
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• v.19 no.11
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• pp.63-72
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• 2014

In this paper, we propose a sign language recognition system using SVM and depth camera. Especially, we focus on the Korean sign language. For the sign language system, we suggest two methods, one in hand feature extraction stage and the other in recognition stage. Hand features are consisted of the number of fingers, finger length, radius of palm, and direction of the hand. To extract hand features, we use Distance Transform and make hand skeleton. This method is more accurate than a traditional method which uses contours. To recognize hand posture, we develop the decision tree with the hand features. For more accuracy, we use SVM to determine the threshold value in the decision tree. In the experimental results, we show that the suggested method is more accurate and faster when extracting hand features a recognizing hand postures.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.205-211
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• 2009

The Weightless Neural Network(WNN) has the advantage of the processing speed, less computability than weighted neural network which readjusts the weight. Especially, The behavior information such as sequential gesture has many serial correlation. So, It is required the high computability and processing time to recognize. To solve these problem, Many algorithms used that added preprocessing and hardware interface device to reduce the computability and speed. In this paper, we proposed the Ram based Sequential Cumulative Neural Network(SCNN) model which is sign language recognition system without preprocessing and hardware interface. We experimented with using compound words in continuous korean sign language which was input binary image with edge detection from camera. The recognition system of sign language without preprocessing got 93% recognition rate.

• Korean Journal of English Language and Linguistics
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• v.3 no.3
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• pp.411-426
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• 2003

I report on the case of a polyglot ‘savant’ (C), who is mildly autistic, severely apraxic, and of limited intellectual ability; yet who can read, write, speak and understand about twenty languages. I outline his abilities, both verbal and non-verbal, noting the asymmetry between his linguistic ability and his general intellectual inability and, within the former, between his unlimited morphological and lexical prowess as opposed to his limited syntax. I then spell out the implications of these findings for modularity. C's unique profile suggested a further project in which we taught him British Sign Language. I report on this work, paying particular attention to the learning and use of classifiers, and discuss its relevance to the issue of modality: whether the human language faculty is preferentially tied to the oral domain, or is ‘modality-neutral’ as between the spoken and the visual modes.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.831-834
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• 2000

The sign-language tan be used a9 an auxiliary communication means between avatars of different languages. At that time an intelligent communication method can be also utilized to achieve real-time communication, where intelligently coded data (joint angles for arm gestures and action units for facial emotions) are transmitted instead of real pictures. In this paper we design a gesture-emotion keyframe editor to provide the means to get easily the parameter values. To calculate both joint angles of the arms and the hands and to goner-ate the in keyframes realistically, a transformation matrix of inverse kinematics and some kinds of constraints are applied. Also, to edit emotional expressions efficiently, a comic-style facial model having only eyebrows, eyes nose, and mouth is employed. Experimental results show a possibility that the editor could be used for intelligent sign-language image communications between different lan-guages.

• 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 Korean Theatre Studies Association
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• no.52
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• pp.271-317
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• 2014

This essay studied the acting theories of Diderot, Delsarte, Meyerhold, and Artaud to know the historical formation of 'sign acting' and its theoretical and aesthetic appropriateness. The sign acting so far discussed shows the repetitive patterns of idea as follows. The sign acting (1) emphasizes the physical expression such as gesture and movement, (2) assumes that the physical expression functions as a sign evoking special emotion and thought, (3) thus recommends the imitation of the outer sign, (4) uses a tableau for the effective reception of outer sign, (5) aims for the spectator oriented aesthetics as it stresses the result of outer sign rather than the creative process of a role, (6) assumes that the emotional reaction or the intellectual understanding springs from the physical experience, (7) thus emphasizes the physical language rather than speech, (8) can attain the appropriateness of physical language by the recent theories of cognitive science. Besides having such commonness, the sign acting also reveals the individual differences. For instance, the intended sign for Diderot and Delsarte was the sign of emotion, for Meyerhold the stylized sign of circus and acrobatics, and for Artaud the spiritual sign. If Diderot and Meyerhold demands the cool consciousness for the correct sign acting, Artaud's sign acting tends to pursue the state of trance. And if Diderot, Delsarte, and Meyerhold think the sign acting on the level of sensory appeal, Artaud insists that the sign acting should dismantle the spectator's sense. As such the discussion of sign acting shows both recurrent ideas and new visions, forming an unity out of diversity. Perhaps the sign acting is a matter of practice before we consider it as a theory. It is not only supposed to have been existed practically since ancient theatre, but also used by actors consciously and unconsciously in expressing certain emotion and thought. We need to study the sign acting more academically, considering its long history and aesthetic potentials. In fact the sign acting has been an essential element of acting, in spite of bad reputation judging it as a banal and worn-out style. It is true that the sign acting, in the worst case, could produce a stereotypical expression. It was this aspect of sign acting that caused a fierce negative reaction of the realists who sought the natural expression based upon psychological truth. Of course the sign acting has a serious problem when it stays banal and artificial. But we need to see this issue from a different perspective. What is the natural expression of emotion? How is it free from the learned way of expression? In some respect, we use, in reality, a learned expression of emotion that could be accepted socially. For instance, when we attend a funeral, we use the outer sign of mourning gestures learned socially. If a semiotic expression pervades various aspects of our life, the acting, being the representation of life, seems not to be free from codified expression. The sign acting could be used consciously and unconsciously in all kinds of acting.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.301-303
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• 2007

This paper presents user adaptation methods to overcome limitations of a user-independent model and a user-dependent model in a Korean sign language recognition system. To adapt model parameters for unobserved states in hidden Markov models, we introduce new methods based on motion similarity and prediction from adaptation history so that we can achieve faster adaption and higher recognition rates comparing with previous methods.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.5
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• pp.32-44
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• 2002

In this paper, we propose TV caption-based KSL(Korean Sign Language) generation system. Through TV caption decoder, this caption signal is transmitted to PC. Next, caption signal is segmented into meaning units by morphological analyzer in considering specific characteristics of Korean sign language. Finally, 3D KSL generation system represents the transformed morphological information by 3D visual graphics. Specifically, we propose a morphological analyzer with many pre-processing techniques for real-time capability. Our developed system is applied to real TV caption program. Through usage of the deaf, we conclude that our system is sufficiently usable compared to conventional TV caption program.

• Journal of IKEEE
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• v.18 no.2
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• pp.291-297
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• 2014

Since hand gesture recognition was realized thanks to improved image processing algorithms, sign language translation has been a critical issue for the hearing-impaired. In this paper, we extract human hand figures from a real time image stream and detect gestures in order to figure out which kind of hand language it means. We used depth-color calibrated image from the Kinect to extract human hands and made a decision tree in order to recognize the hand gesture. The decision tree contains information such as number of fingers, contours, and the hand's position inside a uniform sized image. We succeeded in recognizing 'Hangul', the Korean alphabet, with a recognizing rate of 98.16%. The average execution time per letter of the system was about 76.5msec, a reasonable speed considering hand language translation is based on almost still images. We expect that this research will help communication between the hearing-impaired and other people who don't know hand language.