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2nd International Conference on Convergent Information Technology, ICCIT 07

作者： Oh, Young-Joon Park, Kwang-Hyun Bien, Zeungnam Human-friendly Welfare Robot System Engineering Research Center Korea Advanced Institute of Science and Technology Dept. of Electrical Engineering and Computer Science Korea Advanced Institute of Science and Technology

ISBN: (纸本)0769530389

Sign language is complex visual-spatial language most used in deaf society, and is a representative example of hand gesture with linguistic structure. Korean manual alphabet is a manual alphabet that expresses the vowel and the consonant of Korean sign language. This paper presents a system which recognizes the Korean manual alphabet (KMA) using a USB camera and translates into a normal Korean character. The system captures images from a camera and extracts skin color region from an image, and finds a hand region. The system detects a skin colored hand without particular cloth in a complex background. We use 33 KMA hand shapes as template images, and the system compares hand shape with template images using a correlation coefficient method and composes a text syllable of initial consonant, medial vowel and final consonant. © 2007 IEEE.

关键词： Cameras

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SOFT COMPUTING TECHNIQUE APPROACH TO BUILD A ‘PERSONALIZED' FACIAL EXPRESSION RECOGNITION system

SOFT COMPUTING TECHNIQUE APPROACH TO BUILD A ‘PERSONALIZED'...

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第11届国际模糊系统协会世界大会

作者： Dae-Jin Kim Zeungnam Bien Human-friendly Welfare Robot System-Engineering Research Center(HWRS-ERC) KAIST Korea Human-friendly Welfare Robot System-Engineering Research Center(HWRS-ERC) KAIST Korea

In this paper, we discuss about a design process of 'personalized' classifier with soft computing techniques. Based on a human's way of thinking, a buildup strategy for personalized classifier is denoted. Here, soft computing techniques such as fuzzy logic theory, neural networks and others are effectively used. 'Model Selection' and 'Feature Selection' provide a systematic way to make a set of 'personalized' classifiers. As one of the interesting applications, facial expression recognition problem is discussed. The numerical result shows that the proposed method can enhance the classification rate as high as 94.3%.

关键词： Facial Expression Recognition, Personalization, Fuzzy Similarity Measure, Feature Selection

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Feature set extraction algorithm based on soft computing techniques and its application to EMG pattern classification

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Fuzzy Optimization and Decision Making 2002年第3期1卷 269-286页

作者： Han, Jeong-Su Bang, Won-Chul Bien, Z. Zenn Human-friendly Welfare Robot System Engineering Research Center KAIST 373-1 Guseong-dong Yuseong-gu Daejeon 305-701 Korea Republic of Dept. of Electrical Engineering and Computer Science KAIST 373-1 Guseong-dong Yuseong-gu Daejeon 305-701 Korea Republic of

Recognizing bio-signals, such as EMG, EEG, EOG and ECG, is a promising theme of study since it provides with a convenient means for human-machine interaction. Various approaches of determining features of bio-signals were known for discerning predefined motions/intentions of human, but most of them are applicable mostly only to a single subject, due to inherent characteristics of bio-signals. Lately, several new types of pattern classifier with known features have been proposed to cope with the problem of subject-dependency, but their error rates are still conspicuous when accommodating multiple subjects. Based on the soft computing techniques, this paper presents a comparative experimental study to minimize the subject-dependency. It is shown that the induced feature vector set obtained by the proposed algorithm has less subject-dependency than other existing methods. © 2002 Kluwer Academic Publishers.

关键词： Pattern recognition

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Effective intention reading technique as a means of human-robot interaction for human centered systems

Effective intention reading technique as a means of human-ro...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Dae-Jin Kim Won-Kyung Song Jeong-Su Han Zeungnam Bien Department of Electrical Engineering and Computer Science KAIST Taejon South Korea Human-friendly Welfare Robotic System-Engineering Research Center Taejon South Korea

human-robot interaction technologies are very important components in the human centered system. Among many human-robot interaction technologies, the intention reading of a user plays an important role in human centered systems. In the paper, we focus on the use of intention reading in rehabilitation robots, and implement its capability for the wheelchair-based robotic arm system, called KARES (KAIST Rehabilitation engineering Service system) II. For effective intention reading, visual servoing by using an image sequence of user's face or control by using EMG signals of user's arm are applied to KARES II. Specially, it is shown that soft computing techniques are very effective for intention reading.

关键词： human robot interaction systems engineering and theory Mobile robots Rehabilitation robotics Computer science Visual servoing Image sequences Electromyography Time varying systems Fuzzy systems

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Adaptivity and Learning in human-in-the-Loop systems

Adaptivity and Learning in Human-in-the-Loop Systems

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首届亚洲机械电子学学术会议

作者： Zeungnam Bien Dae-Jin Kim Human-friendly Welfare Robotic System Engineering Research Center(HWRS-ERC) KAIST 373-1 Guseong-dong Yuseong-gu Daejeon 305-701 Korea Human-friendly Welfare Robotic System Engineering Research Center(HWRS-ERC) KAIST 373-1 Guseong-dong Yuseong-gu Daejeon 305-701 Korea

human-in-the-Loop system(HiLS) consists of humans,physical parts with necessary sensors in which a human can be an operator,user or just a being to be *** the con- ventional approach to minimize human factors in HiLS,a‘human-centered’approach accommodate human factors in a feedback *** this pa- per,the notion is reviewed first with some real world *** to our experience,po- tentially usable structures for HiLS must have an adaptivity and learning *** a powerful paradigm,a soft computing technique-based struc- ture is ***,among many possible examples of HiLS with adaptivity and learning ca- pability,the facial emotional emotional expression recognition(FEER)problem is ***- ically,1)Fuzzy observer-based approach,2)per- sonalized FEER system based on fuzzy neural net- works,and 3)Gabor wavelet neural networks are briefly introduced.

关键词： human-in-the-loop system humancentered system facial emotional expression recognition soft computing techniques

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Fuzzy neural networks(FNN)-based approach for personalized facial expression recognition with novel feature selection method

Fuzzy neural networks(FNN)-based approach for personalized f...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Dae-Jin Kim Zeungnam Bien Kwang-Hyun Park Division of EE Department of EECS KAIST Daejeon South Korea Human-friendly Welfare Robotic System Engineering Research Center KAIST Daejeon South Korea

ISBN: (纸本)0780378105

Facial expression recognition is very important in many human-robot/human-computer interaction systems. Although so many researches are done, it is hard to find a practical applications in the real world due to its underestimate about individual differences among people. Thus, as a solution for such problem, we introduce a 'personalized' facial expression recognition system. Many previous works on facial expression recognition focus on the well-known six universal facial expressions (happy, sad, fear, angry, surprise and disgust) under usage of unified (or non-separated) classification approach. However, for ordinary people, it is a very difficult task to make such facial expressions without much effort and training. Instead of universal facial expressions, many people show 'personalized' or 'individualized' facial expressions typically. Thus, for dealing with such personalities, we propose a method to construct a personalized classifier based on novel feature selection method. Specifically, feature selection is done by histogram-based approach in the frame of fuzzy neural networks(FNN). Besides, we also use an integrated approach for facial expression recognition. Actual experiments/simulations show that the proposed method is effective not only in view of facial expression recognition but also in view of pattern classifier itself.

关键词： Fuzzy neural networks Neural networks Face recognition Pattern recognition Computer networks systems engineering and theory human robot interaction Man machine systems Expert systems Histograms

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Training of feature extractor via new cluster validity application to adaptive facial expression recognition

Training of feature extractor via new cluster validity appli...

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9th International Conference on Knowledge-Based Intelligent Information and engineering systems, KES 2005

作者： Lee, Sang Wan Kim, Dae-Jin Kim, Yong Soo Bien, Zeungnam Department of Electrical Engineering and Computer Science KAIST Daejeon 305-701 Korea Republic of Human-friendly Welfare Robot System Engineering Research Center KAIST Daejeon 305-701 Korea Republic of Division of Computer Engineering Daejeon University Daejeon 300-716 Korea Republic of

ISBN: (纸本)354028897X

A lot of researches on classifiers, which can perform well with a given set of feature vectors, have been done. However, researches on feature vectors, which extract better feature vectors automatically, have not been done very much. We face two problems when we consider feature extraction process. One is how we can make a good feature extractor, and the other is what more separable features are. In this paper, we solved these two problems by proposing feature extractor-training methodology that uses new cluster validity as an objective function. By combining feature extractor to Fuzzy Neural Network Model, we achieve on-line adaptation capability as well as optimized feature extraction. The result shows recognition rate of 97% when on-line adaptation is being done. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Face recognition

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Facial Emotional Expression Recognition with Soft Computing Techniques

Facial Emotional Expression Recognition with Soft Computing ...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Dae-Jin Kim Sang-Wan Lee Zeungnam Bien Human-friendly Welfare Robot System Engineering Research Center (HWRS-ERC) Department of EECS KAIST Daejeon South Korea

The facial expression recognition (FER) is one of the biosignal-based recognition techniques which attract a lot of attention recently. To deal with its complex characteristics effectively, we adopt the soft computing techniques (SCT) such as fuzzy logic, neural networks, genetic algorithm and/or rough set technique. In this paper, we overview the state-of-the-art reports on FER in view of SCT, and introduce some interesting works done by our group on the SCT-based facial emotional expression recognition. Specifically, 1) fuzzy observer-based approach, 2) personalized FER system based on fuzzy neural networks, and 3) Gabor wavelet neural networks are briefly discussed

关键词： Emotion recognition Face recognition Neural networks Fuzzy neural networks Artificial neural networks Computer networks humans Feature extraction Neurons Robots

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Multi sensors-based approach for intention reading with soft computing techniques

Multi sensors-based approach for intention reading with soft...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Zeungnam Bien Dae-Jin Kim Hyong-Euk Lee Kwang-Hyun Park Haiying She C. Martens A. Graser Division of EE Department of EECS KAIST Daejeon South Korea Human-friendly Welfare Robotic System Engineering Research Center KAIST Daejeon South Korea Institute of Automation University of Brethemen Bremen Germany

human's intention plays a key role in human-machine interaction as in the case of a robot serving for a handicapped person. The quality of a service robot will be much enhanced if the robot can infer the human's intension during the interaction process. In this paper, we propose a soft computing-based technique to read a user's intention using some multisensors-based approach. We have tested the technique by a scenario of 'serving a drink to the user'. With such force/torque or vision sensor, the robot can effectively infer the user's intention to drink the beverage or not to drink. As an application, this intention technique is employed for building a rehabilitation robot, called KARES II, to perform various human-friendly human-robot interaction.

关键词： Robot sensing systems Rehabilitation robotics human robot interaction robotics and automation Mobile robots Service robots systems engineering and theory Testing Robot vision systems Mouth

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A study on vision-based robust hand-posture recognition by learning similarity between hand-posture and structure

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2nd International Conference on Natural Computation, ICNC 2006

作者： Hyoyoung, Jang Jin-Woo, Jung Zeungnam, Bien Department of Electrical Engineering and Computer Science KAIST 373-1 Guesong-dong Yuseong-gu Daejeon 305-701 Korea Republic of Human-Friendly Welfare Robot System Research Center KAIST 373-1 Guesong-dong Yuseong-gu Daejeon 305-701 Korea Republic of

ISBN: (纸本)3540459073

This paper proposes a robust hand-posture recognition method by learning similarity between hand-posture and structure for the performance improvement of vision-based hand-posture recognition. The difficulties in vision-based hand-posture recognition lie in viewing direction dependency and self-occlusion problem due to the high degree-of-freedom of human hand. General approaches to deal with these problems include multiple camera approach and methods of limiting the relative angle between cameras and the user's hand. In the case of using multiple cameras, however, fusion techniques to induce the final decision should be considered. Limiting the angle of user's hand restricts the user's freedom. The proposed method combines angular features and appearance features to describe hand-postures by a two-layered data structure and includes learning the similarity between the two types of features. The validity of the proposed method is evaluated by applying it to the hand-posture recognition system using three cameras. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Gesture recognition

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