• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.49-58
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• 2011

Owing to the spread of smart devices using touch screen, the Korean language (Hangul) input methods have been varied. In this paper, we have researched and analyzed for finding the best input way of Hangul, which is appropriate to smart devices. By using automata theory, we have suggested easy and efficient automata. The automata, which we suggested, can be used in a Hangul input of gesture type.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.186-191
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• 2015

Hand gesture is the most common tool used to interact with and control various electronic devices. In this paper, we propose a novel hand gesture recognition method using fuzzy logic based classification with a new type of sensor array. In some cases, feature patterns of hand gesture signals cannot be uniquely distinguished and recognized when people perform the same gesture in different ways. Moreover, differences in the hand shape and skeletal articulation of the arm influence to the process. Manifold features were extracted, and efficient features, which make gestures distinguishable, were selected. However, there exist similar feature patterns across different hand gestures, and fuzzy logic is applied to classify them. Fuzzy rules are defined based on the many feature patterns of the input signal. An adaptive neural fuzzy inference system was used to generate fuzzy rules automatically for classifying hand gestures using low number of feature patterns as input. In addition, emotion expression was conducted after the hand gesture recognition for resultant human-robot interaction. Our proposed method was tested with many hand gesture datasets and validated with different evaluation metrics. Experimental results show that our method detects more hand gestures as compared to the other existing methods with robust hand gesture recognition and corresponding emotion expressions, in real time.

• Journal of Information Processing Systems
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• v.6 no.3
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• pp.347-358
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• 2010

This paper presents a measurement system for 3D hand-drawn gesture motion. Many pen-type input devices with Inertial Measurement Units (IMU) have been developed to estimate 3D hand-drawn gesture using the measured acceleration and/or the angular velocity of the device. The crucial procedure in developing these devices is to measure and to analyze their motion or trajectory. In order to verify the trajectory estimated by an IMU-based input device, it is necessary to compare the estimated trajectory to the real trajectory. For measuring the real trajectory of the pen-type device, a PHANToMTM haptic device is utilized because it allows us to measure the 3D motion of the object in real-time. Even though the PHANToMTM measures the position of the hand gesture well, poor initialization may produce a large amount of error. Therefore, this paper proposes a calibration method which can minimize measurement errors.

• Journal of the Ergonomics Society of Korea
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• v.31 no.5
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• pp.629-636
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• 2012

Objective: The purpose of this study is to compare the characteristics of single and double finger gestures related on the web browser and to extract the appropriate finger gestures. Background: As electronic equipment emphasizes miniaturization for improving portability various interfaces are being developed as input devices. Electronic devices are made smaller, the gesture recognition technology using the touch-based interface is favored for easy editing. In addition, user focus primarily on the simplicity of intuitive interfaces which propels further research of gesture based interfaces. In particular, the fingers in these intuitive interfaces are simple and fast which are users friendly. Recently, the single and double finger gestures are becoming more popular so more applications for these gestures are being developed. However, systems and software that employ such finger gesture lack consistency in addition to having unclear standard and guideline development. Method: In order to learn the application of these gestures, we performed the sketch map method which happens to be a method for memory elicitation. In addition, we used the MIMA(Meaning in Mediated Action) method to evaluate gesture interface. Results: This study created appropriate gestures for intuitive judgment. We conducted a usability test which consisted of single and double finger gestures. The results showed that double finger gestures had less performance time faster than single finger gestures. Single finger gestures are a wide satisfaction difference between similar type and difference type. That is, single finger gestures can judge intuitively in a similar type but it is difficult to associate functions in difference type. Conclusion: This study was found that double finger gesture was effective to associate functions for web navigations. Especially, this double finger gesture could be effective on associating complex forms such as curve shaped gestures. Application: This study aimed to facilitate the design products which utilized finger and hand gestures.

• Journal of the Ergonomics Society of Korea
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• v.34 no.5
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• pp.411-426
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• 2015

Objective: The goal of this thesis is to design the interaction structure and framework of system to recognize sign language. Background: The sign language of meaningful individual gestures is combined to construct a sentence, so it is difficult to interpret and recognize the meaning of hand gesture for system, because of the sequence of continuous gestures. This being so, in order to interpret the meaning of individual gesture correctly, the interaction structure and framework are needed so that they can segment the indication of individual gesture. Method: We analyze 700 sign language words to structuralize the sign language gesture interaction. First of all, we analyze the transformational patterns of the hand gesture. Second, we analyze the movement of the transformational patterns of the hand gesture. Third, we analyze the type of other gestures except hands. Based on this, we design a framework for sign language interaction. Results: We elicited 8 patterns of hand gesture on the basis of the fact on whether the gesture has a change from starting point to ending point. And then, we analyzed the hand movement based on 3 elements: patterns of movement, direction, and whether hand movement is repeating or not. Moreover, we defined 11 movements of other gestures except hands and classified 8 types of interaction. The framework for sign language interaction, which was designed based on this mentioned above, applies to more than 700 individual gestures of the sign language, and can be classified as an individual gesture in spite of situation which has continuous gestures. Conclusion: This study has structuralized in 3 aspects defined to analyze the transformational patterns of the starting point and the ending point of hand shape, hand movement, and other gestures except hands for sign language interaction. Based on this, we designed the framework that can recognize the individual gestures and interpret the meaning more accurately, when meaningful individual gesture is input sequence of continuous gestures. Application: When we develop the system of sign language recognition, we can apply interaction framework to it. Structuralized gesture can be used for using database of sign language, inventing an automatic recognition system, and studying on the action gestures in other areas.

• MALSORI
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• no.58
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• pp.101-117
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• 2006

The development of efficient multimodal interfaces and fusion algorithms requires knowledge of usage patterns that show how people use multiple modalities. We analyzed multimodal usage patterns for TV-guide application scenarios (or tasks). In order to collect usage patterns, we implemented a multimodal usage pattern collection system having two input modalities: speech and touch-gesture. Fifty-four subjects participated in our study. Analysis of the collected usage patterns shows a positive correlation between the task type and multimodal usage patterns. In addition, we analyzed the timing between speech-utterances and their corresponding touch-gestures that shows the touch-gesture occurring time interval relative to the duration of speech utterance. We believe that, for developing efficient multimodal fusion algorithms on an application, the multimodal usage pattern analysis for the given application, similar to our work for TV guide application, have to be done in advance.

• Archives of design research
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• v.16 no.2
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• pp.131-140
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• 2003

The input for computer interaction design is very limited for the users to control the interface by only using keyboard and mouse. However, using the basic electrical engineering, the input design can be different from the existing method. Interactive art using computer technology is recently emersed, which is completed by people's participation. The electric signal transmitted in digital and analogue type from the interface controled by people to the computer can be used in multimedia interaction design. The electric circuit design will be necessary to transmit very safe electric signal from the interface. Electric switch, sensor, and camera technologies can be applied to input interface design, which would be alternative physical interaction without computer keyboard and mouse. This type of interaction design using human's body language and gesture would convey the richness of humanity.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.1
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• pp.57-64
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• 2016

Pen-based interaction is universally available on smart devices and especially on Tablet PCs. Previous studies compared various input methods like fingers, a mouse or a stylus pen on PCs or on a touchscreen based devices such as smart phones. At the same time, various soft keyboard applications are being developed on application stores of smart devices. However, these previous studies did not suggest which one is a suitable keyboard application for Tablet PCs when users perform a certain interaction as input type. In this study, we compared two types of input methods (finger and pen) and three types of soft keyboard applications (QWERTY, Gesture and Swype) in a Tablet PC using performance measurements (accuracy and input speed) and discussed what types of applications showed better performance with each interaction on tablet PC. From these results, recommendations for the keyboard types depending on the input methods on tablet PCs were developed.

• Journal of the Ergonomics Society of Korea
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• v.35 no.6
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• pp.519-533
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• 2016

Objective: This study lays its aims at the definition of relevant operation method and function by researching on the value to be brought when applying smart device that can hand carry soft and flexible materials like jelly. Background: New technology and material play a role in bringing type transformation of interface and change of operation system. Recently, importance has been increased on the study of Organic User Interface (OUI) that conducts research on the value of new method of input and output adopting soft and flexible materials for various instruments. Method: For fulfillment of the study, 27 kinds of gestures have been defined that are usable in handheld device based on existing studies. Quantitative research of survey was conducted of adult male and female of 20s through 30s and an analysis was done on the function that can be linked to gestures with highest level of satisfaction. In order to analyze needs and hurdles of users for the defined gesture, a focus group interview was conducted aiming at the groups of early adopters and ordinary users. Results: As a result, it was found that users have much value regarding usability and fun for elastic device and analysis could be conducted on preferred gesture and its linkable functions. Conclusion: What is most significant with this study is that it sheds new light on the values of a device made of elastic material. Beyond finding and defining the gestures and functions that can be applied to a handheld elastic device, the present study identified the value elements of an elastic device - 'usability and 'fun' -, which users can basically desire from using it. Application: The data that this study brought forth through preference and satisfaction test with the gestures and associated functions will help commercialize an elastic device in future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1770-1776
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• 2021

For hand expression recognition, hand pose recognition based on the static shape of the hand and hand gesture recognition based on hand movement are used together. In this paper, we proposed a hand expression recognition method that recognizes symbols based on the trajectory of a hand movement on a virtual blackboard. In order to recognize a sign drawn by hand on a virtual blackboard, not only a method of recognizing a sign from a hand movement, but also hand pose recognition for finding the start and end of data input is also required. In this paper, MediaPipe was used to recognize hand pose, and LSTM(Long Short Term Memory), a type of recurrent neural network, was used to recognize hand gesture from time series data. To verify the effectiveness of the proposed method, it was applied to the recognition of numbers written on a virtual blackboard, and a recognition rate of about 94% was obtained.